Bioequivalence and Bioavailability Forum

lsmeans() & lme() [🇷 for BE/BA]

posted by Helmut  – Vienna, Austria, 2015-04-20 03:28 (3715 d 00:06 ago) – Posting: # 14711
Views: 28,809

Hi Yung-jin,

funny – while you posted I experimented with lsmeans as well. Not so bad.

❝ lsmeans only work with lmer(), not lme().

That’s not correct – see help(models)!

Hint: If in a replicate design evaluated by a mixed effects model the SEs of R and T are equal, likely something is wrong with the coding.

I hijacked your RepMIX() and renamed to honor ElMaestro.
# Change to directory containing "SingleRep_stat_demo.csv" first!
# setwd("E:/Public/Documents/BEBAC/bear/")
library(nlme)
library(lsmeans)
cnames <- c("subj", "drug", "seq", "prd", "Cmax",
  "AUC0t","AUC0INF","lnCmax","lnAUC0t","lnAUC0INF")
TotalData <- read.csv("SingleRep_stat_demo.csv",
  header=T, row.names=NULL, col.names=cnames, sep=",", dec=".")
TotalData[, !(names(TotalData) %in% c("AUC0t", "AUC0INF", "lnCmax",
  "lnAUC0t","lnAUC0INF"))] muddle <- lme(log(Cmax) ~ drug+seq+prd, random = ~drug-1|subj,
  data=TotalData)
lsmeans(muddle, "drug", cov.reduce=F, weights="equal")

 drug   lsmean         SE df lower.CL upper.CL
    1 7.328141 0.02504047 12 7.273582 7.382699
    2 7.391880 0.03485385 12 7.315940 7.467820

Results are averaged over the levels of: seq, prd
Confidence level used: 0.95

Bingo for the means! The SEs are still off (compared to PHX).
Level Estimate StdError DF
  R   7.328141 0.039852 12
  T   7.391880 0.032656 12
At least something to start from.

---

Post #500 this year.

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Helmut Schütz


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Complete thread:

• Reproducing Bear results in Phoenix mittyri 2015-04-14 08:35 [🇷 for BE/BA] 
  • Bug in bear? Helmut 2015-04-14 14:07
    • Bug in bear? mittyri 2015-04-14 20:43
      • Bug in bear? Helmut 2015-04-15 02:17
    • use the same dataset? yjlee168 2015-04-20 10:13
  • Bugs in bear with replicated demo data set? yjlee168 2015-04-15 09:38
  • Bugs fixed in bear? yjlee168 2015-04-17 01:21
    • Bugs fixed in bear? Helmut 2015-04-17 14:25
      • Bugs fixed in bear? yjlee168 2015-04-17 18:50
        • Bugs fixed in bear? ElMaestro 2015-04-17 23:14
          • lme() in bear yjlee168 2015-04-18 11:12
            • lme() in bear ElMaestro 2015-04-18 11:28
              • lme() in bear yjlee168 2015-04-18 12:02
                • lme() in bear ElMaestro 2015-04-18 13:42
                  • Mean means Helmut 2015-04-18 14:08
                    • Mean means ElMaestro 2015-04-18 16:01
                      • Mean means Helmut 2015-04-19 00:59
                        • Mean means ElMaestro 2015-04-19 09:14
                          • LL and AIC Helmut 2015-04-19 11:08
                            • Confused ElMaestro 2015-04-19 11:42
                        • lsmeans for mixed model in R yjlee168 2015-04-19 23:36
                          • lsmeans() & lme()Helmut 2015-04-20 01:28
                            • lsmeans() & lme() yjlee168 2015-04-20 10:23
                            • lsmeans() & lme() ElMaestro 2015-04-20 10:35
                              • keep it simple! Helmut 2015-04-20 14:34
                                • keep it simple! ElMaestro 2015-04-20 15:39
                                  • ML vs. REML Helmut 2015-04-20 16:35
            • lme() with NA in R yjlee168 2015-04-19 23:44
        • Dataset Helmut 2015-04-18 13:30
          • Dataset and lme() in bear yjlee168 2015-04-18 23:14