# Could the Odds represent weight in Generalized Linear Model?

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## Could the Odds represent weight in Generalized Linear Model?

 Hello all, I'm sorry if my question seems basic. Im studying a responses (Yes,No) in a survey and, thanks to GLM I obtain the following relation with my variables : (Yes,No)~ β0 + Age We note this this certain type of (Yes,No) response is linked to age (p<0.05 in glm) . After that we calculated : model1=glm(cbind(Yes,No) ~ Age + Times + Type, family=binomial) summary(model1) exp(model1$coefficients) exp(model1$coefficients)(Intercept)         Age       Times TypeRegular  0.01659381  1.02546748  1.01544154  1.70056425 The odds of answering 'Yes' is multiplied with 1.02 for each additional year of age. My questions is : (1) it is possible to add to my model, (Yes,No)~ β0 + Age, the weight of the variable Age. Is it in fact the odd value ? Here is an example : is it ok to formulate my model as that (Yes,No)~ β0 + 1.02* Age: here 1.02 is what I call weight of age, in other words, I want to quantify its impact in the model. (2)suppose I want to model (Yes,No)~ β0 + Type with type a categorical data. odd value of TypeRegular is 1.70056425. But in my model it is simply Type that include Regular and Irregular. How to adapt this value to Type ? My data res=structure(list(Age = c(10, 14, 14, 15, 16, 16, 16, 17, 17, 17, 17, 18, 18, 18, 18, 18, 18, 18, 18, 19, 19, 19, 19, 19, 19, 19, 19, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 21, 21, 21, 21, 21, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 23, 23, 23, 23, 23, 24, 24, 24, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 27, 27, 27, 27, 27, 27, 27, 27, 27, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 29, 29, 29, 29, 29, 29, 29, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 31, 31, 31, 31, 31, 31, 31, 31, 32, 32, 32, 32, 32, 32, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 33, 34, 34, 34, 34, 34, 34, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 36, 36, 36, 36, 36, 36, 36, 36, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 38, 38, 38, 38, 38, 38, 38, 38, 38, 38, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 40, 40, 40, 40, 40, 40, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 43, 43, 43, 43, 43, 43, 43, 43, 43, 43, 43, 43, 44, 44, 44, 44, 44, 44, 44, 44, 44, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 45, 46, 46, 46, 46, 46, 46, 46, 46, 47, 47, 47, 47, 47, 47, 47, 47, 48, 48, 48, 48, 48, 48, 48, 49, 49, 49, 49, 49, 49, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 51, 51, 51, 51, 51, 51, 51, 51, 51, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 54, 54, 54, 54, 54, 54, 54, 54, 54, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 55, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, 57, 57, 57, 57, 57, 57, 57, 57, 57, 58, 58, 58, 58, 58, 58, 58, 59, 59, 59, 59, 59, 59, 60, 60, 60, 60, 60, 60, 60, 61, 62, 62, 62, 62, 63, 64, 64, 65, 65, 67, 74), Times = c(6L, 6L, 16L, 6L, 9L, 23L, 33L, 6L, 14L, 17L, 36L, 4L, 9L, 15L, 20L, 26L, 28L, 30L, 33L, 6L, 11L, 14L, 20L, 26L, 28L, 30L, 32L, 4L, 4L, 6L, 9L, 17L, 26L, 28L, 30L, 33L, 44L, 47L, 4L, 6L, 23L, 26L, 32L, 4L, 9L, 11L, 11L, 14L, 14L, 15L, 17L, 18L, 20L, 23L, 26L, 36L, 44L, 50L, 4L, 9L, 28L, 30L, 32L, 4L, 17L, 23L, 4L, 6L, 9L, 9L, 11L, 14L, 25L, 33L, 33L, 51L, 4L, 6L, 14L, 17L, 18L, 26L, 28L, 30L, 32L, 33L, 44L, 50L, 6L, 9L, 9L, 11L, 14L, 17L, 22L, 23L, 30L, 4L, 9L, 11L, 14L, 15L, 20L, 23L, 28L, 29L, 36L, 39L, 43L, 51L, 58L, 14L, 20L, 23L, 26L, 28L, 36L, 51L, 4L, 6L, 9L, 16L, 17L, 18L, 23L, 33L, 37L, 51L, 9L, 11L, 14L, 18L, 23L, 26L, 28L, 58L, 9L, 17L, 33L, 36L, 37L, 58L, 4L, 6L, 9L, 9L, 11L, 17L, 20L, 26L, 28L, 32L, 33L, 47L, 4L, 6L, 9L, 15L, 23L, 28L, 4L, 9L, 9L, 15L, 17L, 18L, 20L, 23L, 28L, 30L, 30L, 4L, 6L, 6L, 9L, 17L, 18L, 33L, 36L, 4L, 6L, 11L, 14L, 15L, 17L, 23L, 26L, 28L, 36L, 4L, 6L, 9L, 11L, 17L, 18L, 23L, 25L, 28L, 30L, 6L, 9L, 11L, 14L, 14L, 17L, 20L, 23L, 28L, 35L, 44L, 4L, 6L, 9L, 14L, 17L, 44L, 6L, 9L, 14L, 17L, 22L, 26L, 28L, 29L, 33L, 36L, 50L, 4L, 6L, 6L, 17L, 20L, 23L, 28L, 30L, 36L, 51L, 58L, 4L, 9L, 9L, 14L, 15L, 17L, 23L, 26L, 28L, 30L, 36L, 38L, 6L, 6L, 9L, 17L, 23L, 26L, 28L, 43L, 44L, 4L, 15L, 17L, 17L, 25L, 26L, 28L, 36L, 44L, 51L, 58L, 6L, 9L, 16L, 25L, 28L, 32L, 44L, 58L, 4L, 9L, 17L, 28L, 30L, 36L, 43L, 44L, 6L, 11L, 14L, 16L, 26L, 30L, 44L, 15L, 20L, 23L, 26L, 28L, 52L, 4L, 6L, 9L, 9L, 11L, 14L, 16L, 17L, 20L, 23L, 26L, 28L, 30L, 33L, 35L, 37L, 50L, 51L, 6L, 9L, 14L, 17L, 18L, 18L, 26L, 44L, 50L, 9L, 14L, 14L, 15L, 18L, 20L, 23L, 28L, 33L, 36L, 43L, 44L, 50L, 4L, 9L, 11L, 14L, 18L, 26L, 28L, 29L, 30L, 32L, 43L, 44L, 52L, 6L, 9L, 20L, 23L, 28L, 30L, 33L, 36L, 43L, 4L, 9L, 11L, 14L, 16L, 20L, 23L, 26L, 28L, 36L, 50L, 51L, 4L, 6L, 9L, 14L, 18L, 23L, 26L, 30L, 36L, 43L, 44L, 52L, 6L, 9L, 17L, 18L, 23L, 26L, 28L, 30L, 35L, 9L, 14L, 20L, 32L, 33L, 36L, 44L, 6L, 9L, 23L, 25L, 36L, 51L, 9L, 17L, 17L, 18L, 20L, 33L, 58L, 9L, 23L, 26L, 28L, 36L, 6L, 20L, 28L, 20L, 23L, 4L, 15L), Type = c("Regular", "Regular", "Irregular", "Regular", "Regular", "Irregular", "Regular", "Irregular", "Irregular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Irregular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Irregular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Irregular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular"), Yes = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), No = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 0L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 3L, 0L, 1L, 1L, 1L, 1L, 1L, 5L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 3L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 1L, 2L, 2L, 5L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 0L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 3L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 5L, 1L, 1L, 0L, 3L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 3L, 2L, 1L, 2L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 2L, 1L, 1L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 2L, 1L, 1L, 0L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 3L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 0L, 2L, 4L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L)), .Names = c("Age", "Times", "Type", "Yes", "No"), row.names = c(NA, -426L), class = "data.frame") Thansk a lot for your help. Lenny Garanti sans virus. www.avg.com <#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2>         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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## Re: Could the Odds represent weight in Generalized Linear Model?

 Dear Lenny, You can do this by using Age as an offset factor. dataset$wAge <- dataset$Age * 1.02 glm(cbind(Yes,No) ~ offset(wAge) + Times + Type, family=binomial, data = dataset) Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance [hidden email] Havenlaan 88 bus 73, 1000 Brussel www.inbo.be /////////////////////////////////////////////////////////////////////////////////////////// To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey /////////////////////////////////////////////////////////////////////////////////////////// 2018-01-30 11:14 GMT+01:00 contact retour-client < [hidden email]>: > Hello all, > > > I'm sorry if my question seems basic. > > Im studying a responses (Yes,No) in a survey and, thanks to GLM I obtain > the following relation with my variables : (Yes,No)~ β0 + Age We note this > this certain type of (Yes,No) response is linked to age (p<0.05 in glm) . > > After that we calculated : > > model1=glm(cbind(Yes,No) ~ Age + Times + Type, family=binomial) > summary(model1) > exp(model1$coefficients) > > exp(model1$coefficients)(Intercept)         Age       Times TypeRegular >  0.01659381  1.02546748  1.01544154  1.70056425 > > The odds of answering 'Yes' is multiplied with 1.02 for each additional > year of age. > > My questions is : > > (1) it is possible to add to my model, (Yes,No)~ β0 + Age, the weight of > the variable Age. Is it in fact the odd value ? Here is an example : is it > ok to formulate my model as that (Yes,No)~ β0 + 1.02* Age: here 1.02 is > what I call weight of age, in other words, I want to quantify its impact in > the model. > > (2)suppose I want to model (Yes,No)~ β0 + Type with type a categorical > data. odd value of TypeRegular is 1.70056425. But in my model it is simply > Type that include Regular and Irregular. How to adapt this value to Type ? > > My data > > res=structure(list(Age = c(10, 14, 14, 15, 16, 16, 16, 17, 17, 17, 17, > 18, 18, 18, 18, 18, 18, 18, 18, 19, 19, 19, 19, 19, 19, 19, 19, 20, > 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 21, 21, 21, 21, 21, 22, 22, > 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 23, 23, 23, 23, > 23, 24, 24, 24, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 26, 26, 26, > 26, 26, 26, 26, 26, 26, 26, 26, 26, 27, 27, 27, 27, 27, 27, 27, 27, > 27, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 29, 29, > 29, 29, 29, 29, 29, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 31, 31, > 31, 31, 31, 31, 31, 31, 32, 32, 32, 32, 32, 32, 33, 33, 33, 33, 33, > 33, 33, 33, 33, 33, 33, 33, 34, 34, 34, 34, 34, 34, 35, 35, 35, 35, > 35, 35, 35, 35, 35, 35, 35, 36, 36, 36, 36, 36, 36, 36, 36, 37, 37, > 37, 37, 37, 37, 37, 37, 37, 37, 38, 38, 38, 38, 38, 38, 38, 38, 38, > 38, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 40, 40, 40, 40, 40, > 40, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 42, 42, 42, 42, 42, > 42, 42, 42, 42, 42, 42, 43, 43, 43, 43, 43, 43, 43, 43, 43, 43, 43, > 43, 44, 44, 44, 44, 44, 44, 44, 44, 44, 45, 45, 45, 45, 45, 45, 45, > 45, 45, 45, 45, 46, 46, 46, 46, 46, 46, 46, 46, 47, 47, 47, 47, 47, > 47, 47, 47, 48, 48, 48, 48, 48, 48, 48, 49, 49, 49, 49, 49, 49, 50, > 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, > 51, 51, 51, 51, 51, 51, 51, 51, 51, 52, 52, 52, 52, 52, 52, 52, 52, > 52, 52, 52, 52, 52, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, > 53, 54, 54, 54, 54, 54, 54, 54, 54, 54, 55, 55, 55, 55, 55, 55, 55, > 55, 55, 55, 55, 55, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, > 57, 57, 57, 57, 57, 57, 57, 57, 57, 58, 58, 58, 58, 58, 58, 58, 59, > 59, 59, 59, 59, 59, 60, 60, 60, 60, 60, 60, 60, 61, 62, 62, 62, 62, > 63, 64, 64, 65, 65, 67, 74), Times = c(6L, 6L, 16L, 6L, 9L, 23L, 33L, > 6L, 14L, 17L, 36L, 4L, 9L, 15L, 20L, 26L, 28L, 30L, 33L, 6L, 11L, 14L, > 20L, 26L, 28L, 30L, 32L, 4L, 4L, 6L, 9L, 17L, 26L, 28L, 30L, 33L, 44L, > 47L, 4L, 6L, 23L, 26L, 32L, 4L, 9L, 11L, 11L, 14L, 14L, 15L, 17L, 18L, > 20L, 23L, 26L, 36L, 44L, 50L, 4L, 9L, 28L, 30L, 32L, 4L, 17L, 23L, 4L, > 6L, 9L, 9L, 11L, 14L, 25L, 33L, 33L, 51L, 4L, 6L, 14L, 17L, 18L, 26L, > 28L, 30L, 32L, 33L, 44L, 50L, 6L, 9L, 9L, 11L, 14L, 17L, 22L, 23L, > 30L, 4L, 9L, 11L, 14L, 15L, 20L, 23L, 28L, 29L, 36L, 39L, 43L, 51L, > 58L, 14L, 20L, 23L, 26L, 28L, 36L, 51L, 4L, 6L, 9L, 16L, 17L, 18L, > 23L, 33L, 37L, 51L, 9L, 11L, 14L, 18L, 23L, 26L, 28L, 58L, 9L, 17L, > 33L, 36L, 37L, 58L, 4L, 6L, 9L, 9L, 11L, 17L, 20L, 26L, 28L, 32L, 33L, > 47L, 4L, 6L, 9L, 15L, 23L, 28L, 4L, 9L, 9L, 15L, 17L, 18L, 20L, 23L, > 28L, 30L, 30L, 4L, 6L, 6L, 9L, 17L, 18L, 33L, 36L, 4L, 6L, 11L, 14L, > 15L, 17L, 23L, 26L, 28L, 36L, 4L, 6L, 9L, 11L, 17L, 18L, 23L, 25L, > 28L, 30L, 6L, 9L, 11L, 14L, 14L, 17L, 20L, 23L, 28L, 35L, 44L, 4L, 6L, > 9L, 14L, 17L, 44L, 6L, 9L, 14L, 17L, 22L, 26L, 28L, 29L, 33L, 36L, > 50L, 4L, 6L, 6L, 17L, 20L, 23L, 28L, 30L, 36L, 51L, 58L, 4L, 9L, 9L, > 14L, 15L, 17L, 23L, 26L, 28L, 30L, 36L, 38L, 6L, 6L, 9L, 17L, 23L, > 26L, 28L, 43L, 44L, 4L, 15L, 17L, 17L, 25L, 26L, 28L, 36L, 44L, 51L, > 58L, 6L, 9L, 16L, 25L, 28L, 32L, 44L, 58L, 4L, 9L, 17L, 28L, 30L, 36L, > 43L, 44L, 6L, 11L, 14L, 16L, 26L, 30L, 44L, 15L, 20L, 23L, 26L, 28L, > 52L, 4L, 6L, 9L, 9L, 11L, 14L, 16L, 17L, 20L, 23L, 26L, 28L, 30L, 33L, > 35L, 37L, 50L, 51L, 6L, 9L, 14L, 17L, 18L, 18L, 26L, 44L, 50L, 9L, > 14L, 14L, 15L, 18L, 20L, 23L, 28L, 33L, 36L, 43L, 44L, 50L, 4L, 9L, > 11L, 14L, 18L, 26L, 28L, 29L, 30L, 32L, 43L, 44L, 52L, 6L, 9L, 20L, > 23L, 28L, 30L, 33L, 36L, 43L, 4L, 9L, 11L, 14L, 16L, 20L, 23L, 26L, > 28L, 36L, 50L, 51L, 4L, 6L, 9L, 14L, 18L, 23L, 26L, 30L, 36L, 43L, > 44L, 52L, 6L, 9L, 17L, 18L, 23L, 26L, 28L, 30L, 35L, 9L, 14L, 20L, > 32L, 33L, 36L, 44L, 6L, 9L, 23L, 25L, 36L, 51L, 9L, 17L, 17L, 18L, > 20L, 33L, 58L, 9L, 23L, 26L, 28L, 36L, 6L, 20L, 28L, 20L, 23L, 4L, > 15L), Type = c("Regular", "Regular", "Irregular", "Regular", > "Regular", "Irregular", "Regular", "Irregular", "Irregular", > "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", > "Irregular", "Regular", "Irregular", "Regular", "Regular", "Regular", > "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", > "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Irregular", "Regular", "Irregular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", > "Regular", "Irregular", "Regular", "Regular", "Regular", "Irregular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Irregular", "Regular", "Irregular", > "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", > "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Irregular", "Irregular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", > "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Irregular", "Irregular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Irregular", "Regular", "Irregular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Irregular", "Irregular", "Irregular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", > "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Irregular", "Regular", "Regular", "Regular", "Irregular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", > "Irregular", "Regular", "Regular", "Regular", "Irregular", "Regular", > "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", > "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", > "Regular", "Irregular", "Regular", "Regular"), Yes = c(0L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, > 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, > 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, > 0L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, > 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, > 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, > 1L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, > 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, > 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, > 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, > 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, > 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), No = c(1L, > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, > 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 0L, 1L, 1L, 1L, 1L, > 2L, 1L, 1L, 1L, 1L, 1L, 3L, 0L, 1L, 1L, 1L, 1L, 1L, 5L, 1L, 1L, 1L, > 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 3L, 1L, 2L, 1L, 1L, > 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, > 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, > 3L, 1L, 2L, 2L, 5L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 0L, 1L, 1L, 1L, 2L, > 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, > 1L, 1L, 3L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 1L, 1L, 0L, 0L, > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 5L, 1L, 1L, 0L, 3L, > 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 3L, 2L, 1L, 2L, 0L, 1L, 1L, 1L, 0L, > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, > 1L, 1L, 1L, 1L, 1L, 0L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, > 0L, 1L, 1L, 1L, 0L, 1L, 2L, 1L, 1L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, > 1L, 1L, 0L, 0L, 1L, 1L, 1L, 2L, 1L, 1L, 0L, 1L, 2L, 1L, 2L, 1L, 1L, > 1L, 2L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, > 1L, 1L, 1L, 1L, 3L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, > 1L, 1L, 0L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 0L, 2L, 4L, 1L, 3L, 1L, 1L, > 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, > 2L, 2L, 2L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, > 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, > 1L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L)), > .Names = c("Age", "Times", "Type", "Yes", "No"), row.names = c(NA, > -426L), class = "data.frame") > > Thansk a lot for your help. > > > Lenny > > utm_source=link&utm_campaign=sig-email&utm_content=webmail> > Garanti > sans virus. www.avg.com > utm_source=link&utm_campaign=sig-email&utm_content=webmail> > <#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2> > >         [[alternative HTML version deleted]] > > ______________________________________________ > [hidden email] mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide http://www.R-project.org/> posting-guide.html > and provide commented, minimal, self-contained, reproducible code.         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
 Dear Thierry, Thanks a lot for this answer, I mean i want to obtain such model *Behavior1 = β0+β1*Age* , the purpose is to obtain  *β1*. I want to be sure that the odds value could be the  β1. Or how to calculate it ? Thanks again for your precious help. Lenny Garanti sans virus. www.avg.com <#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2> 2018-01-30 15:37 GMT+01:00 Thierry Onkelinx <[hidden email]>: > Dear Lenny, > > You can do this by using Age as an offset factor. > > dataset$wAge <- dataset$Age * 1.02 > glm(cbind(Yes,No) ~ offset(wAge) + Times + Type, family=binomial, data = > dataset) > > Best regards, > > > > > ir. Thierry Onkelinx > Statisticus / Statistician > > Vlaamse Overheid / Government of Flanders > INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND > FOREST > Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance > [hidden email] > Havenlaan 88 > bus 73, > 1000 Brussel > www.inbo.be > > //////////////////////////////////////////////////////////// > /////////////////////////////// > To call in the statistician after the experiment is done may be no more > than asking him to perform a post-mortem examination: he may be able to say > what the experiment died of. ~ Sir Ronald Aylmer Fisher > The plural of anecdote is not data. ~ Roger Brinner > The combination of some data and an aching desire for an answer does not > ensure that a reasonable answer can be extracted from a given body of data. > ~ John Tukey > //////////////////////////////////////////////////////////// > /////////////////////////////// > > > > 2018-01-30 11:14 GMT+01:00 contact retour-client < > [hidden email]>: > >> Hello all, >> >> >> I'm sorry if my question seems basic. >> >> Im studying a responses (Yes,No) in a survey and, thanks to GLM I obtain >> the following relation with my variables : (Yes,No)~ β0 + Age We note this >> this certain type of (Yes,No) response is linked to age (p<0.05 in glm) . >> >> After that we calculated : >> >> model1=glm(cbind(Yes,No) ~ Age + Times + Type, family=binomial) >> summary(model1) >> exp(model1$coefficients) >> >> exp(model1$coefficients)(Intercept)         Age       Times TypeRegular >>  0.01659381  1.02546748  1.01544154  1.70056425 >> >> The odds of answering 'Yes' is multiplied with 1.02 for each additional >> year of age. >> >> My questions is : >> >> (1) it is possible to add to my model, (Yes,No)~ β0 + Age, the weight of >> the variable Age. Is it in fact the odd value ? Here is an example : is it >> ok to formulate my model as that (Yes,No)~ β0 + 1.02* Age: here 1.02 is >> what I call weight of age, in other words, I want to quantify its impact >> in >> the model. >> >> (2)suppose I want to model (Yes,No)~ β0 + Type with type a categorical >> data. odd value of TypeRegular is 1.70056425. But in my model it is simply >> Type that include Regular and Irregular. How to adapt this value to Type ? >> >> My data >> >> res=structure(list(Age = c(10, 14, 14, 15, 16, 16, 16, 17, 17, 17, 17, >> 18, 18, 18, 18, 18, 18, 18, 18, 19, 19, 19, 19, 19, 19, 19, 19, 20, >> 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 21, 21, 21, 21, 21, 22, 22, >> 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 23, 23, 23, 23, >> 23, 24, 24, 24, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 26, 26, 26, >> 26, 26, 26, 26, 26, 26, 26, 26, 26, 27, 27, 27, 27, 27, 27, 27, 27, >> 27, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 29, 29, >> 29, 29, 29, 29, 29, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 31, 31, >> 31, 31, 31, 31, 31, 31, 32, 32, 32, 32, 32, 32, 33, 33, 33, 33, 33, >> 33, 33, 33, 33, 33, 33, 33, 34, 34, 34, 34, 34, 34, 35, 35, 35, 35, >> 35, 35, 35, 35, 35, 35, 35, 36, 36, 36, 36, 36, 36, 36, 36, 37, 37, >> 37, 37, 37, 37, 37, 37, 37, 37, 38, 38, 38, 38, 38, 38, 38, 38, 38, >> 38, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 40, 40, 40, 40, 40, >> 40, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 42, 42, 42, 42, 42, >> 42, 42, 42, 42, 42, 42, 43, 43, 43, 43, 43, 43, 43, 43, 43, 43, 43, >> 43, 44, 44, 44, 44, 44, 44, 44, 44, 44, 45, 45, 45, 45, 45, 45, 45, >> 45, 45, 45, 45, 46, 46, 46, 46, 46, 46, 46, 46, 47, 47, 47, 47, 47, >> 47, 47, 47, 48, 48, 48, 48, 48, 48, 48, 49, 49, 49, 49, 49, 49, 50, >> 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, >> 51, 51, 51, 51, 51, 51, 51, 51, 51, 52, 52, 52, 52, 52, 52, 52, 52, >> 52, 52, 52, 52, 52, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, >> 53, 54, 54, 54, 54, 54, 54, 54, 54, 54, 55, 55, 55, 55, 55, 55, 55, >> 55, 55, 55, 55, 55, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, >> 57, 57, 57, 57, 57, 57, 57, 57, 57, 58, 58, 58, 58, 58, 58, 58, 59, >> 59, 59, 59, 59, 59, 60, 60, 60, 60, 60, 60, 60, 61, 62, 62, 62, 62, >> 63, 64, 64, 65, 65, 67, 74), Times = c(6L, 6L, 16L, 6L, 9L, 23L, 33L, >> 6L, 14L, 17L, 36L, 4L, 9L, 15L, 20L, 26L, 28L, 30L, 33L, 6L, 11L, 14L, >> 20L, 26L, 28L, 30L, 32L, 4L, 4L, 6L, 9L, 17L, 26L, 28L, 30L, 33L, 44L, >> 47L, 4L, 6L, 23L, 26L, 32L, 4L, 9L, 11L, 11L, 14L, 14L, 15L, 17L, 18L, >> 20L, 23L, 26L, 36L, 44L, 50L, 4L, 9L, 28L, 30L, 32L, 4L, 17L, 23L, 4L, >> 6L, 9L, 9L, 11L, 14L, 25L, 33L, 33L, 51L, 4L, 6L, 14L, 17L, 18L, 26L, >> 28L, 30L, 32L, 33L, 44L, 50L, 6L, 9L, 9L, 11L, 14L, 17L, 22L, 23L, >> 30L, 4L, 9L, 11L, 14L, 15L, 20L, 23L, 28L, 29L, 36L, 39L, 43L, 51L, >> 58L, 14L, 20L, 23L, 26L, 28L, 36L, 51L, 4L, 6L, 9L, 16L, 17L, 18L, >> 23L, 33L, 37L, 51L, 9L, 11L, 14L, 18L, 23L, 26L, 28L, 58L, 9L, 17L, >> 33L, 36L, 37L, 58L, 4L, 6L, 9L, 9L, 11L, 17L, 20L, 26L, 28L, 32L, 33L, >> 47L, 4L, 6L, 9L, 15L, 23L, 28L, 4L, 9L, 9L, 15L, 17L, 18L, 20L, 23L, >> 28L, 30L, 30L, 4L, 6L, 6L, 9L, 17L, 18L, 33L, 36L, 4L, 6L, 11L, 14L, >> 15L, 17L, 23L, 26L, 28L, 36L, 4L, 6L, 9L, 11L, 17L, 18L, 23L, 25L, >> 28L, 30L, 6L, 9L, 11L, 14L, 14L, 17L, 20L, 23L, 28L, 35L, 44L, 4L, 6L, >> 9L, 14L, 17L, 44L, 6L, 9L, 14L, 17L, 22L, 26L, 28L, 29L, 33L, 36L, >> 50L, 4L, 6L, 6L, 17L, 20L, 23L, 28L, 30L, 36L, 51L, 58L, 4L, 9L, 9L, >> 14L, 15L, 17L, 23L, 26L, 28L, 30L, 36L, 38L, 6L, 6L, 9L, 17L, 23L, >> 26L, 28L, 43L, 44L, 4L, 15L, 17L, 17L, 25L, 26L, 28L, 36L, 44L, 51L, >> 58L, 6L, 9L, 16L, 25L, 28L, 32L, 44L, 58L, 4L, 9L, 17L, 28L, 30L, 36L, >> 43L, 44L, 6L, 11L, 14L, 16L, 26L, 30L, 44L, 15L, 20L, 23L, 26L, 28L, >> 52L, 4L, 6L, 9L, 9L, 11L, 14L, 16L, 17L, 20L, 23L, 26L, 28L, 30L, 33L, >> 35L, 37L, 50L, 51L, 6L, 9L, 14L, 17L, 18L, 18L, 26L, 44L, 50L, 9L, >> 14L, 14L, 15L, 18L, 20L, 23L, 28L, 33L, 36L, 43L, 44L, 50L, 4L, 9L, >> 11L, 14L, 18L, 26L, 28L, 29L, 30L, 32L, 43L, 44L, 52L, 6L, 9L, 20L, >> 23L, 28L, 30L, 33L, 36L, 43L, 4L, 9L, 11L, 14L, 16L, 20L, 23L, 26L, >> 28L, 36L, 50L, 51L, 4L, 6L, 9L, 14L, 18L, 23L, 26L, 30L, 36L, 43L, >> 44L, 52L, 6L, 9L, 17L, 18L, 23L, 26L, 28L, 30L, 35L, 9L, 14L, 20L, >> 32L, 33L, 36L, 44L, 6L, 9L, 23L, 25L, 36L, 51L, 9L, 17L, 17L, 18L, >> 20L, 33L, 58L, 9L, 23L, 26L, 28L, 36L, 6L, 20L, 28L, 20L, 23L, 4L, >> 15L), Type = c("Regular", "Regular", "Irregular", "Regular", >> "Regular", "Irregular", "Regular", "Irregular", "Irregular", >> "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", >> "Irregular", "Regular", "Irregular", "Regular", "Regular", "Regular", >> "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", >> "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Irregular", "Regular", "Irregular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", >> "Regular", "Irregular", "Regular", "Regular", "Regular", "Irregular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Irregular", "Regular", "Irregular", >> "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", >> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Irregular", "Irregular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", >> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Irregular", "Irregular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Irregular", "Regular", "Irregular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Irregular", "Irregular", "Irregular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", >> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Irregular", "Regular", "Regular", "Regular", "Irregular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >> "Irregular", "Regular", "Regular", "Regular", "Irregular", "Regular", >> "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", >> "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", >> "Regular", "Irregular", "Regular", "Regular"), Yes = c(0L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, >> 0L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, >> 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, >> 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, >> 1L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, >> 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), No = c(1L, >> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, >> 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 0L, 1L, 1L, 1L, 1L, >> 2L, 1L, 1L, 1L, 1L, 1L, 3L, 0L, 1L, 1L, 1L, 1L, 1L, 5L, 1L, 1L, 1L, >> 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 3L, 1L, 2L, 1L, 1L, >> 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, >> 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, >> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, >> 3L, 1L, 2L, 2L, 5L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 0L, 1L, 1L, 1L, 2L, >> 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, >> 1L, 1L, 3L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, >> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 1L, 1L, 0L, 0L, >> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 5L, 1L, 1L, 0L, 3L, >> 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 3L, 2L, 1L, 2L, 0L, 1L, 1L, 1L, 0L, >> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, >> 1L, 1L, 1L, 1L, 1L, 0L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, >> 0L, 1L, 1L, 1L, 0L, 1L, 2L, 1L, 1L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >> 1L, 1L, 0L, 0L, 1L, 1L, 1L, 2L, 1L, 1L, 0L, 1L, 2L, 1L, 2L, 1L, 1L, >> 1L, 2L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, >> 1L, 1L, 1L, 1L, 3L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, >> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, >> 1L, 1L, 0L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 0L, 2L, 4L, 1L, 3L, 1L, 1L, >> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >> 2L, 2L, 2L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >> 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, >> 1L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L)), >> .Names = c("Age", "Times", "Type", "Yes", "No"), row.names = c(NA, >> -426L), class = "data.frame") >> >> Thansk a lot for your help. >> >> >> Lenny >> >> > source=link&utm_campaign=sig-email&utm_content=webmail> >> Garanti >> sans virus. www.avg.com >> > source=link&utm_campaign=sig-email&utm_content=webmail> >> <#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2> >> >>         [[alternative HTML version 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 Dear Lenny, \beta_1 is the log odds ratio for age. If you want the odds ratio, then you need to calculate it. It looks like some reading up on glm won't harm you. Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance [hidden email] Havenlaan 88 bus 73, 1000 Brussel www.inbo.be /////////////////////////////////////////////////////////////////////////////////////////// To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey /////////////////////////////////////////////////////////////////////////////////////////// 2018-01-30 15:46 GMT+01:00 contact retour-client <[hidden email]>: > Dear Thierry, > > Thanks a lot for this answer, > > I mean i want to obtain such model Behavior1 = β0+β1*Age , the purpose is to > obtain  β1. I want to be sure that the odds value could be the  β1. Or how > to calculate it ? > > Thanks again for your precious help. > > Lenny > > Garanti sans virus. www.avg.com > > 2018-01-30 15:37 GMT+01:00 Thierry Onkelinx <[hidden email]>: >> >> Dear Lenny, >> >> You can do this by using Age as an offset factor. >> >> dataset$wAge <- dataset$Age * 1.02 >> glm(cbind(Yes,No) ~ offset(wAge) + Times + Type, family=binomial, data = >> dataset) >> >> Best regards, >> >> >> >> >> ir. Thierry Onkelinx >> Statisticus / Statistician >> >> Vlaamse Overheid / Government of Flanders >> INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND >> FOREST >> Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance >> [hidden email] >> Havenlaan 88 bus 73, 1000 Brussel >> www.inbo.be >> >> >> /////////////////////////////////////////////////////////////////////////////////////////// >> To call in the statistician after the experiment is done may be no more >> than asking him to perform a post-mortem examination: he may be able to say >> what the experiment died of. ~ Sir Ronald Aylmer Fisher >> The plural of anecdote is not data. ~ Roger Brinner >> The combination of some data and an aching desire for an answer does not >> ensure that a reasonable answer can be extracted from a given body of data. >> ~ John Tukey >> >> /////////////////////////////////////////////////////////////////////////////////////////// >> >> >> >> 2018-01-30 11:14 GMT+01:00 contact retour-client >> <[hidden email]>: >>> >>> Hello all, >>> >>> >>> I'm sorry if my question seems basic. >>> >>> Im studying a responses (Yes,No) in a survey and, thanks to GLM I obtain >>> the following relation with my variables : (Yes,No)~ β0 + Age We note >>> this >>> this certain type of (Yes,No) response is linked to age (p<0.05 in glm) . >>> >>> After that we calculated : >>> >>> model1=glm(cbind(Yes,No) ~ Age + Times + Type, family=binomial) >>> summary(model1) >>> exp(model1$coefficients) >>> >>> exp(model1$coefficients)(Intercept)         Age       Times TypeRegular >>>  0.01659381  1.02546748  1.01544154  1.70056425 >>> >>> The odds of answering 'Yes' is multiplied with 1.02 for each additional >>> year of age. >>> >>> My questions is : >>> >>> (1) it is possible to add to my model, (Yes,No)~ β0 + Age, the weight of >>> the variable Age. Is it in fact the odd value ? Here is an example : is >>> it >>> ok to formulate my model as that (Yes,No)~ β0 + 1.02* Age: here 1.02 is >>> what I call weight of age, in other words, I want to quantify its impact >>> in >>> the model. >>> >>> (2)suppose I want to model (Yes,No)~ β0 + Type with type a categorical >>> data. odd value of TypeRegular is 1.70056425. But in my model it is >>> simply >>> Type that include Regular and Irregular. How to adapt this value to Type >>> ? >>> >>> My data >>> >>> res=structure(list(Age = c(10, 14, 14, 15, 16, 16, 16, 17, 17, 17, 17, >>> 18, 18, 18, 18, 18, 18, 18, 18, 19, 19, 19, 19, 19, 19, 19, 19, 20, >>> 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 21, 21, 21, 21, 21, 22, 22, >>> 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 23, 23, 23, 23, >>> 23, 24, 24, 24, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 26, 26, 26, >>> 26, 26, 26, 26, 26, 26, 26, 26, 26, 27, 27, 27, 27, 27, 27, 27, 27, >>> 27, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 29, 29, >>> 29, 29, 29, 29, 29, 30, 30, 30, 30, 30, 30, 30, 30, 30, 30, 31, 31, >>> 31, 31, 31, 31, 31, 31, 32, 32, 32, 32, 32, 32, 33, 33, 33, 33, 33, >>> 33, 33, 33, 33, 33, 33, 33, 34, 34, 34, 34, 34, 34, 35, 35, 35, 35, >>> 35, 35, 35, 35, 35, 35, 35, 36, 36, 36, 36, 36, 36, 36, 36, 37, 37, >>> 37, 37, 37, 37, 37, 37, 37, 37, 38, 38, 38, 38, 38, 38, 38, 38, 38, >>> 38, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 39, 40, 40, 40, 40, 40, >>> 40, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 41, 42, 42, 42, 42, 42, >>> 42, 42, 42, 42, 42, 42, 43, 43, 43, 43, 43, 43, 43, 43, 43, 43, 43, >>> 43, 44, 44, 44, 44, 44, 44, 44, 44, 44, 45, 45, 45, 45, 45, 45, 45, >>> 45, 45, 45, 45, 46, 46, 46, 46, 46, 46, 46, 46, 47, 47, 47, 47, 47, >>> 47, 47, 47, 48, 48, 48, 48, 48, 48, 48, 49, 49, 49, 49, 49, 49, 50, >>> 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, >>> 51, 51, 51, 51, 51, 51, 51, 51, 51, 52, 52, 52, 52, 52, 52, 52, 52, >>> 52, 52, 52, 52, 52, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, 53, >>> 53, 54, 54, 54, 54, 54, 54, 54, 54, 54, 55, 55, 55, 55, 55, 55, 55, >>> 55, 55, 55, 55, 55, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, >>> 57, 57, 57, 57, 57, 57, 57, 57, 57, 58, 58, 58, 58, 58, 58, 58, 59, >>> 59, 59, 59, 59, 59, 60, 60, 60, 60, 60, 60, 60, 61, 62, 62, 62, 62, >>> 63, 64, 64, 65, 65, 67, 74), Times = c(6L, 6L, 16L, 6L, 9L, 23L, 33L, >>> 6L, 14L, 17L, 36L, 4L, 9L, 15L, 20L, 26L, 28L, 30L, 33L, 6L, 11L, 14L, >>> 20L, 26L, 28L, 30L, 32L, 4L, 4L, 6L, 9L, 17L, 26L, 28L, 30L, 33L, 44L, >>> 47L, 4L, 6L, 23L, 26L, 32L, 4L, 9L, 11L, 11L, 14L, 14L, 15L, 17L, 18L, >>> 20L, 23L, 26L, 36L, 44L, 50L, 4L, 9L, 28L, 30L, 32L, 4L, 17L, 23L, 4L, >>> 6L, 9L, 9L, 11L, 14L, 25L, 33L, 33L, 51L, 4L, 6L, 14L, 17L, 18L, 26L, >>> 28L, 30L, 32L, 33L, 44L, 50L, 6L, 9L, 9L, 11L, 14L, 17L, 22L, 23L, >>> 30L, 4L, 9L, 11L, 14L, 15L, 20L, 23L, 28L, 29L, 36L, 39L, 43L, 51L, >>> 58L, 14L, 20L, 23L, 26L, 28L, 36L, 51L, 4L, 6L, 9L, 16L, 17L, 18L, >>> 23L, 33L, 37L, 51L, 9L, 11L, 14L, 18L, 23L, 26L, 28L, 58L, 9L, 17L, >>> 33L, 36L, 37L, 58L, 4L, 6L, 9L, 9L, 11L, 17L, 20L, 26L, 28L, 32L, 33L, >>> 47L, 4L, 6L, 9L, 15L, 23L, 28L, 4L, 9L, 9L, 15L, 17L, 18L, 20L, 23L, >>> 28L, 30L, 30L, 4L, 6L, 6L, 9L, 17L, 18L, 33L, 36L, 4L, 6L, 11L, 14L, >>> 15L, 17L, 23L, 26L, 28L, 36L, 4L, 6L, 9L, 11L, 17L, 18L, 23L, 25L, >>> 28L, 30L, 6L, 9L, 11L, 14L, 14L, 17L, 20L, 23L, 28L, 35L, 44L, 4L, 6L, >>> 9L, 14L, 17L, 44L, 6L, 9L, 14L, 17L, 22L, 26L, 28L, 29L, 33L, 36L, >>> 50L, 4L, 6L, 6L, 17L, 20L, 23L, 28L, 30L, 36L, 51L, 58L, 4L, 9L, 9L, >>> 14L, 15L, 17L, 23L, 26L, 28L, 30L, 36L, 38L, 6L, 6L, 9L, 17L, 23L, >>> 26L, 28L, 43L, 44L, 4L, 15L, 17L, 17L, 25L, 26L, 28L, 36L, 44L, 51L, >>> 58L, 6L, 9L, 16L, 25L, 28L, 32L, 44L, 58L, 4L, 9L, 17L, 28L, 30L, 36L, >>> 43L, 44L, 6L, 11L, 14L, 16L, 26L, 30L, 44L, 15L, 20L, 23L, 26L, 28L, >>> 52L, 4L, 6L, 9L, 9L, 11L, 14L, 16L, 17L, 20L, 23L, 26L, 28L, 30L, 33L, >>> 35L, 37L, 50L, 51L, 6L, 9L, 14L, 17L, 18L, 18L, 26L, 44L, 50L, 9L, >>> 14L, 14L, 15L, 18L, 20L, 23L, 28L, 33L, 36L, 43L, 44L, 50L, 4L, 9L, >>> 11L, 14L, 18L, 26L, 28L, 29L, 30L, 32L, 43L, 44L, 52L, 6L, 9L, 20L, >>> 23L, 28L, 30L, 33L, 36L, 43L, 4L, 9L, 11L, 14L, 16L, 20L, 23L, 26L, >>> 28L, 36L, 50L, 51L, 4L, 6L, 9L, 14L, 18L, 23L, 26L, 30L, 36L, 43L, >>> 44L, 52L, 6L, 9L, 17L, 18L, 23L, 26L, 28L, 30L, 35L, 9L, 14L, 20L, >>> 32L, 33L, 36L, 44L, 6L, 9L, 23L, 25L, 36L, 51L, 9L, 17L, 17L, 18L, >>> 20L, 33L, 58L, 9L, 23L, 26L, 28L, 36L, 6L, 20L, 28L, 20L, 23L, 4L, >>> 15L), Type = c("Regular", "Regular", "Irregular", "Regular", >>> "Regular", "Irregular", "Regular", "Irregular", "Irregular", >>> "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", >>> "Irregular", "Regular", "Irregular", "Regular", "Regular", "Regular", >>> "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Irregular", >>> "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Irregular", "Regular", "Irregular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", >>> "Regular", "Irregular", "Regular", "Regular", "Regular", "Irregular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Irregular", "Regular", "Irregular", >>> "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Irregular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", >>> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Irregular", "Irregular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", >>> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Irregular", "Irregular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Irregular", "Regular", "Irregular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Irregular", "Irregular", "Irregular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", >>> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Irregular", "Regular", "Regular", "Regular", "Irregular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Irregular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Irregular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Irregular", "Regular", "Regular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Regular", "Regular", "Regular", >>> "Irregular", "Regular", "Regular", "Regular", "Irregular", "Regular", >>> "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", >>> "Regular", "Regular", "Regular", "Irregular", "Regular", "Regular", >>> "Regular", "Irregular", "Regular", "Regular"), Yes = c(0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, >>> 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, >>> 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, >>> 1L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, >>> 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, >>> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >>> 0L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), No = c(1L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, >>> 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 0L, 1L, 1L, 1L, 1L, >>> 2L, 1L, 1L, 1L, 1L, 1L, 3L, 0L, 1L, 1L, 1L, 1L, 1L, 5L, 1L, 1L, 1L, >>> 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 3L, 1L, 2L, 1L, 1L, >>> 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, >>> 3L, 1L, 2L, 2L, 5L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 0L, 1L, 1L, 1L, 2L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, >>> 1L, 1L, 3L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 2L, 1L, 1L, 1L, 1L, 0L, 0L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 5L, 1L, 1L, 0L, 3L, >>> 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 3L, 2L, 1L, 2L, 0L, 1L, 1L, 1L, 0L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 3L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 0L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, >>> 0L, 1L, 1L, 1L, 0L, 1L, 2L, 1L, 1L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >>> 1L, 1L, 0L, 0L, 1L, 1L, 1L, 2L, 1L, 1L, 0L, 1L, 2L, 1L, 2L, 1L, 1L, >>> 1L, 2L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, >>> 1L, 1L, 1L, 1L, 3L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, >>> 1L, 1L, 0L, 3L, 1L, 1L, 1L, 1L, 1L, 2L, 0L, 2L, 4L, 1L, 3L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >>> 2L, 2L, 2L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >>> 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, >>> 1L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L)), >>> .Names = c("Age", "Times", "Type", "Yes", "No"), row.names = c(NA, >>> -426L), class = "data.frame") >>> >>> Thansk a lot for your help. >>> >>> >>> Lenny >>> >>> >>> >>> Garanti >>> sans virus. www.avg.com >>> >>> >>> <#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2> >>> >>>         [[alternative HTML version deleted]] >>> >>> ______________________________________________ >>> [hidden email] mailing list -- To UNSUBSCRIBE and more, see >>> https://stat.ethz.ch/mailman/listinfo/r-help>>> PLEASE do read the posting guide >>> http://www.R-project.org/posting-guide.html>>> and provide commented, minimal, self-contained, reproducible code. >> >> > ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.