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 thierry.onkel...@inbo.be 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 /////////////////////////////////////////////////////////////////////////////////////////// <https://www.inbo.be> 2018-01-30 11:14 GMT+01:00 contact retour-client < retour.client.cont...@gmail.com>: > 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 > > <http://www.avg.com/email-signature?utm_medium=email&; > utm_source=link&utm_campaign=sig-email&utm_content=webmail> > Garanti > sans virus. www.avg.com > <http://www.avg.com/email-signature?utm_medium=email&; > utm_source=link&utm_campaign=sig-email&utm_content=webmail> > <#DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2> > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org 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. 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