# Conditional logistic regression: within subject matching instead of McNemar [duplicate]

I'm trying to compare the prevalence of a specific lesion (binary) at the symptomatic side to the asymptomatic side within a group of patients.

I've already performed a McNemar test to compare the prevalence at the symptomatic versus asymptomatic side within patients.

However, I'm asked to also perform a conditional logistic regression. I'm not sure if my syntax is correct with respect to the stratification:

summary(clogit(ds$symp ~ ds$asymp, strata(ds$ID), data=ds, method = "exact"))  Question: Does R compare both sides of the patient (symptomatic vs asymptomatic) within the patient(s)? Or do I have to duplicate manually the patient ID (one ID for the symptomatic side AND one ID for the asymptomatic side)? An example: ID symp asymp 1 0 0 2 1 0 3 0 0 4 0 0 5 1 0 6 1 1 7 0 0 8 0 0 9 0 1 10 0 0  As an example: patient 2 has a lesion at the symptomatic side and patient 9 only at the asymptomatic side. Patients 6 at both sides. A Exact McNemar test shows: test <- table(df$symp, df$asymp) compare <- exact2x2(test, paired = TRUE, alternative = "two.sided", tsmethod = "central") print(compare) Exact McNemar test (with central confidence intervals) data: test b = 1, c = 2, p-value = 1 alternative hypothesis: true odds ratio is not equal to 1 95 percent confidence interval: 0.00847498 9.60452988 sample estimates: odds ratio 0.5  However, a conditional logistic regression model shows: > summary(clogit(df$symp ~  df$asymp, strata(df$ID), data=df, method = "exact"))
Call:
coxph(formula = Surv(rep(1, 10L), df$symp) ~ df$asymp, data = df,
method = "exact")

n= 10, number of events= 3

coef exp(coef) se(coef)     z Pr(>|z|)
df$symp 0.973 2.646 1.524 0.638 0.523 exp(coef) exp(-coef) lower .95 upper .95 df$asymp 2.646      0.378    0.1334     52.46

Rsquare= 0.039   (max possible= 0.616 )
Likelihood ratio test= 0.4  on 1 df,   p=0.528
Wald test            = 0.41  on 1 df,   p=0.5232
Score (logrank) test = 0.43  on 1 df,   p=0.5127


Or should I duplicate patients and use the syntax as described above?

ID side   lesion
1   symp    0
1   asymp   1
2   symp    0
2   asymp   0
3   symp    1
3   asymp   0
4   symp    0
4   asymp   0
5   symp    1
5   asymp   1
6   symp    1
6   asymp   0