> lstrends(m1s, ~Type, var="Var", adjust = "tukey", transform="response")
 Type Var.trend      SE  df asymp.LCL asymp.UCL
 A      -0.0289 0.00344 Inf   -0.0357   -0.0222
 B       0.0358 0.00344 Inf    0.0290    0.0425
 C       0.0704 0.00298 Inf    0.0645    0.0762

Trends are obtained after back-transforming from the logit scale
Confidence level used: 0.95

> df <- transform(df, sVar = scale(Var))
> m1pre.s <- glmer(cbind(y, notY) ~ Type * sVar + (1|ID),
+     data=df, family=binomial)

> lstrends(m1pre.s, ~Type, var="sVar", adjust = "tukey", transform="response")
 Type sVar.trend      SE  df asymp.LCL asymp.UCL
 A       -0.0334 0.00396 Inf   -0.0411   -0.0256
 B        0.0412 0.00396 Inf    0.0335    0.0490
 C        0.0812 0.00344 Inf    0.0744    0.0879

Trends are obtained after back-transforming from the logit scale
Confidence level used: 0.95