search for: byear

...m more complicated model. However, when I run LRT to compare them, the test did not return F value and p-value for me. What's the reason? How can I get such important information? #################################################### Analysis of Deviance Table Model 1: sum_surv15 ~ s(FLBS) + s(byear) + s(FLBS, byear) Model 2: sum_surv15 ~ s(FLBS) + SES + s(byear) + s(FLBS, byear) Resid. Df Resid. Dev Df Deviance F Pr(>F) 1 1202.21094 601.27 2 1201.43848 601.29 0.77246 -0.02 #################################################### Thank you v...

...hat is, the codes ?y~z+s(x,by=z)? and ?y~z+s(x,by=z)-1? gave the same results. The following is my result: ########################################################################### ?anova(model1,model2,test="Chisq") Analysis of Deviance Table Model 1: FLBS ~ SES + s(FAFR, by = SES) + s(byear, by = SES) + s(FAFR, byear, by = SES) Model 2: FLBS ~ SES + s(FAFR, by = SES) + s(byear, by = SES) + s(FAFR, byear, by = SES) - 1 Resid. Df Resid. Dev Df Deviance P(>|Chi|) 1 1.2076e+03 1458.4 2 1.2076e+03 1458.4 1.9099e-11 5.030e-10 2.0...

Dear R users, my dataframe looks like this head(dat) Id sex byear age 1 300 m 2003 50 2 300 m 2003 36 3 402 f 2003 29 4 402 f 2003 21 5 402 f 2003 64 6 150 m 2005 43 ... ...(where Id is just the Identification number of Individual, sex (male or female), byear (=birthyear)) now, I 'd like to add a column, where each Individual gets...

hi, I have been trying to do this in R (have implemented it in Excel) but I have been using a very inefficent way (loops etc.). I have matrix A (columns are years and ages are rows) and matrix B (columns are birth yrs and rows are ages) I would like to first turn matrix A into matrix B And then I would like to convert matrix B back again to the original matrix A. (I have left out details of

...kind of variables into my config R file? thank you ################################################ ##########config file ########################### method=1; # amount of methods method1;method2;method3; #name of the method time=6 #time intv byear=1990 #strar year eyear=2010 #end year title = "pictitle" #title xlab = "xlabinfo" #xlab xxlimmin = 0 #x xxlimmax = 100 #x ylab = "ylabinfo"...

...hat if not for interpretation but just for prediction, multicollinearity does not matter much. However, I am using mixed model to interpret something, so I am wondering if there is a suitable method to deal with this problem in lmer. My model is: model2<-lmer(sur_prop~(kidc+I(kidc^2)+I(kidc^3))*(byear_c+I(byear_c^2) +I(byear_c^3)+I(byear_c^4))+(byear_c|Studyparish),family=binomial) This is the maximum model and I have not begun to simplify it. The model is used to interpret the pattern how a mother's cohort year and total number of children will affect average survival rate of her children....