Bioequivalence and Bioavailability Forum • estimate(test-ref) and lsmeans in bear

estimate(test-ref) and lsmeans in bear [🇷 for BE/BA]

posted by mittyri – Russia, 2018-12-12 23:57 (1953 d 04:48 ago) – Posting: # 19688
Views: 11,110

Dear Yung-jin,

Thank you for the explanation.

❝ Estimate(test-ref) in bear is not obtained directly from the difference of mean values or lsmean. It is obtained from one of coefficients of lm() function.

In your example the dataset is balanced.
The question is how do you obtain LSMeans or what do you output as

MEAN-ref = 7.32951 

MEAN-test = 7.40146

❝ please browse "Interpreting regression coefficient in R" for more details (the explanations for the coefficient x32). Does anyone know the name of this coefficient in statistics? Thanks.

That is called as a contrast.

Here's a little code where I show that the LSMeans difference is a point estimate irrespective of the sequence balance.

library(data.table)

library(curl)

library(emmeans)

alpha <- 0.05

PKdf <- fread("https://static-content.springer.com/esm/art%3A10.1208%2Fs12248-014-9661-0/MediaObjects/12248_2014_9661_MOESM1_ESM.txt")

setorder(PKdf, Subj)



factorcols <- colnames(PKdf)[-5]
PKdf[,(factorcols) := lapply(.SD, as.factor), .SDcols = factorcols]


ow <- options()

options(contrasts=c("contr.treatment","contr.poly"))



# get rid of 3 subjects in one sequence

PKdf_1 <- PKdf[which(Subj!=1L&Subj!=2L&Subj!=4L),]


logmeans <- data.frame(PKdf_1[, lapply(.SD, function(x){mean(log(x))}), by = Trt, .SDcols="Var"])

colnames(logmeans) <- c("Trt", "logmean")



muddle   <- lm(log(Var)~Trt+Per+Seq+Subj, data=PKdf_1)



print(table(PKdf_1[, Seq]))

# RT TR 

# 12 18 



# in the standard contrasts option "contr.treatment" 

# the coefficient TrtT is the difference T-R since TrtR is set to zero

lnPE     <- coef(muddle)["TrtT"]
cat("The contrast from lm() is ", lnPE)

# The contrast from lm() is  -0.04975903



print(logmeans)

# Trt  logmean

# 1   T 4.916300

# 2   R 4.980382



# compare with LSMeans

LSMobj <- lsmeans(muddle, 'Trt')

print(cbind.data.frame(Trt = summary(LSMobj)$Trt,LSMean = summary(LSMobj)$lsmean))

#   Trt   LSMean

# 1   R 4.988564

# 2   T 4.938805



cat("LSMeans difference is ", summary(LSMobj)$lsmean[2] - summary(LSMobj)$lsmean[1])

# LSMeans difference is  -0.04975903



LSMpair <- pairs(LSMobj, reverse = T)

cat("The contrast from LSMeans difference is ", summary(LSMpair)$estimate)

# The contrast from LSMeans difference is  -0.04975903





lnCI     <- confint(muddle,c("TrtT"), level=1-2*alpha)

print(lnCI)

# 5 %        95 %

#   TrtT -0.1013179 0.001799863



print(confint(LSMpair, level =0.9))

# contrast    estimate         SE df   lower.CL  upper.CL

# T - R    -0.04975903 0.02911397 13 -0.1013179 0.001799863

# 

# Results are averaged over the levels of: Per, Subj, Seq 

# Results are given on the log (not the response) scale. 

# Confidence level used: 0.9 





#reset options

options(ow)

—
Kind regards,
Mittyri

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