etkileşim Zelig

Question

ilk farklılıklar bu yapıyla bir veri kümesi var Burada

z <- zls$new() 
z$zelig(out ~ time * treatment, data = dat) 
summary(z) 

bir kesilmiş çıktı ...

Coefficients: 
        Estimate Std. Error t value Pr(>|t|) 
(Intercept)  2.40264 0.71552 3.358 0.00081 
time-11   -1.61292 1.08177 -1.491 0.13622 
time-10   -1.03283 0.99850 -1.034 0.30116 
time-9   -1.47934 1.02667 -1.441 0.14987 
time-8   -0.35614 1.02667 -0.347 0.72874 
time-7   -1.05803 1.04304 -1.014 0.31061 
time-6   -2.25316 1.16178 -1.939 0.05269 
.... 
treatment   1.28097 0.89440 1.432 0.15234 
time-11:treatment 2.86965 1.30927 2.192 0.02859 
time-10:treatment 1.69479 1.25788 1.347 0.17813 
time-9:treatment 1.78684 1.27330 1.403 0.16078 
time-8:treatment 0.82332 1.27330 0.647 0.51801 
time-7:treatment 1.62808 1.28334 1.269 0.20482 
time-6:treatment 2.64653 1.36895 1.933 0.05344 
time-5:treatment 3.08572 1.36895 2.254 0.02437 
.... 

Her zaman için ilk farkları (tedavi = 1, tedavi = 0) tahmin etmek istiyorum. o zamana göre etkiler.

Herhangi bir fikrin var mı? Teşekkür ederiz Önceden

Answer 1

Burada bir döngü kullanarak bir çözüm.

m <- zelig(outcome ~ time * treatment, model = "ls", data = dat) 

output <- NULL 

for (i in unique(dat$time)) { 

t0 <- setx(m, treatment = 0, time = i) 
t1 <- setx(m, treatment = 1, time = i) 

ss <- sim(m, x = t0, x1 = t1, num = 10000) 
fd <- unlist(ss$sim.out[["x1"]][["fd"]]) 

r <- data.table(time = i, mean = mean(fd), low = quantile(fd, .025), high = quantile(fd, 0.975)) 
output <- rbind(output, r) 
} 

output 
    time  mean   low  high 
1: -12 1.506365 -0.30605416 3.347631 
2: -11 1.013915 -0.83479749 2.817791 
3: -10 2.673004 0.72371241 4.645537 
4: -9 1.291547 -0.62162353 3.183365 
5: -8 2.985348 0.59834003 5.351312 
6: -7 3.911258 1.95825840 5.878157 
7: -6 4.222870 1.86773822 6.567400 
8: -5 3.152967 0.81620039 5.483884 
9: -4 3.893867 1.77629999 6.003647 
10: -3 2.319123 0.35445149 4.278032 
11: -2 1.942848 0.03771276 3.844245 
12: -1 3.879313 1.92915419 5.852765 
13: 0 1.388601 -0.93881332 3.703387 
14: 1 3.576107 1.54679622 5.567298 
15: 2 2.413652 0.58863014 4.225094 
16: 3 2.160988 0.03251586 4.266438 
17: 4 2.203825 0.28985053 4.080361 
18: 5 4.445642 2.40569051 6.510071 
19: 6 1.504513 -0.27797349 3.251175 
20: 7 2.542558 0.77794333 4.269277 
21: 8 2.682681 0.93322199 4.449863 
22: 9 4.271228 2.39189897 6.137469 
23: 10 2.540004 0.66875643 4.454354 
24: 11 3.454584 1.54938921 5.340096 
25: 12 3.682521 1.85539403 5.501669 
    time  mean   low  high