search for: glsrun2

...nction(x) gls(score.1~I(time-1), data=x, correlation=corAR1(form=~1|V1), method='ML')) # Extract intercepts and slopes int1 <- sapply(glsrun1, function(x) x$coefficient[1]) slo1 <- sapply(glsrun1, function(x) x$coefficient[2]) ################ #Clean up workspace rm(glsrun1) gc() glsrun2 <- lapply(long, function(x) gls(score.2~I(time-1), data=x, correlation=corAR1(form=~1|V1), method='ML')) # Extract intercepts and slopes int2 <- sapply(glsrun2, function(x) x$coefficient[1]) slo2 <- sapply(glsrun2, function(x) x$coefficient[2]) #Clean up workspace rm(glsrun2...

...1", varying=list(c(names(Data[[i]])[2:5]),c(names(Data[[i]])[6:9])), v.names=c("score.1","score.2"), direction="long")) # Step 4 Run GLS glsrun1 <- lapply(long, function(x) gls(score.1~I(time-1), data=x, correlation=corAR1(form=~1|V1), method='ML')) glsrun2 <- lapply(long, function(x) gls(score.2~I(time-1), data=x, correlation=corAR1(form=~1|V1), method='ML')) # Step 5 Extract Intercepts and slopes int1 <- lapply(glsrun1, function(x) x$coefficient[1]) slo1 <- lapply(glsrun1, function(x) x$coefficient[2]) int2 <- lapply(glsrun2, f...

...","X2","X3","X4"),c("X5","X6","X7","X8")), v.names=c("score.1","score.2"),direction='long') glsrun1 <- gls(score.1~I(time-1), data=long, correlation=corAR1(form=~1|ID), method='ML') glsrun2 <- gls(score.2~I(time-1), data=long, correlation=corAR1(form=~1|ID), method='ML') intercept1[[i]] <- glsrun1$coefficient[1] slope1[[i]] <- glsrun1$coefficient[2] intercept2[[i]] <- glsrun2$coefficient[1] slope2[[i]] <- glsrun2$coefficient[2] } cat("Sample Size...