= Conditional logistic regression using R = Taken from Agresti (2002). Fuller details are given [[http://www-stat.stanford.edu/~owen/courses/306a/Splusdiscrete2.pdf|here.]] The below R code is used on the data below (first five case-controls are listed) {{{ > table.10.3 pair MI diabetes 1 1 0 1 2 1 1 1 3 2 0 1 4 2 1 1 5 3 0 1 }}} R code: {{{ library(survival) table.10.3<-data.frame(pair=rep(1:144,rep(2,144)), MI=rep(c(0,1),144), diabetes=c(rep(c(1,1),9),rep(c(1,0),16),rep(c(0,1),37),rep(c(0,0),82)) ) # Can use coxph routine equiavelently to clogit #fit.CLR<-coxph(Surv(rep(1,2*144),MI)~diabetes+strata(pair),method="exact", #data=table.10.3) library(survival) fit.CLR<-clogit(MI~diabetes+strata(pair),method="exact", data=table.10.3) summary(fit.CLR) }}} This gives the output: {{{ Call: clogit(MI ~ diabetes + strata(pair), method = "exact", data = table.10.3) coef exp(coef) se(coef) z p diabetes 0.838 2.31 0.299 2.8 0.0051 Likelihood ratio test=8.55 on 1 df, p=0.00345 n= 288 }}} The clogit procedure (unlike the SPSS Cox model) can be used to stratify ''more'' than two matched observations ie three or more repeated counts on each of n subjects. See for example Whitaker at al. (2005) with accompanying clogit R code from Helen Whitaker's website [[http://statistics.open.ac.uk/sccs|here.]] Xu et al. (2011) suggest a graphical diagnostic tool to choose the best lag time from trigger (e.g. stress) to event (e.g. epileptic seizure) whilst Farrington and Hocine (2010) advocate checking for clustering of events and using only the first event in each cluster to remove bias resulting from correlated events. __References__ Agresti A (2002) Categorical Data Analysis. Second Edition. Wiley:New York. Farrington CP and Hocine MN (2010) Within-individual dependence in self-controlled case series models for recurrent events. ''Applied Statistics'' '''59(3)''' 457-475. A copy is available [[http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9876.2009.00703.x/pdf | here.]] Whitaker HJ, Farrington, CP, Spiessens B. and Musonda P. (2006) Tutorial in biostatistics:the self-controlled case series method. ''Statistics in Medicine'' '''25(1)''' 1768-1797. An earlier 2005 pdf draft of this paper is given [[attachment:selfc.pdf|here.]] [[attachment:xu.pdf | Xu S, Zhang L, Nelson JC, Zeng C, Mullooly J, McClure D and Glanz J]] (2011) ''Statistics in Medicine'' '''30''' 742-752. Plotting to find optimal time at risk for each trigger on an individual.