report.lsmeans: 'LS Means' statistics reporting

In jfrancoiscollin/ClinReport: Statistical Reporting for Scientific Publications, Epidemiological Studies and Clinical Trials

Description

Creates a desc object for "LS Means" statistics reporting.

For more examples see the website: ClinReport website

Usage

report.lsmeans(lsm, at.row = NULL, infer = c(T, T), round = 2, x1,
  x2, x3, x1.name, x2.name, x3.name, data, contrast, contrast.name, type,
  transpose = FALSE, y.label = NULL)

Arguments

lsm	emmGrid object (result of a emmeans call)
at.row	Character. Passed to spacetable function. Used to space the results per levels of the mentioned variable
infer	A vector of one or two logical values. Passed to summary.emmGrid function.
round	Numeric. Specify the number of digits to round the statistics
x1	deprecated
x2	deprecated
x3	deprecated
x1.name	deprecated
x2.name	deprecated
x3.name	deprecated
data	deprecated
contrast	deprecated
contrast.name	deprecated
type	deprecated
transpose	Logical. If TRUE Statistics will be reported in columns
y.label	Character Indicates the label for y parameter to be displayed in the title of the table

Details

You can produce formatted Least Square Means table for up to 3 factors. It doesn't work for quantitative covariates.

See examples below.

Value

A desc object that can be used by the report.doc function.

See Also

report.quali emmeans report.doc desc

Examples

library(emmeans)
library(lme4)

data(datafake)

#Simple lm model

mod=lm(Petal.Width~Species,data=iris)
raw.lsm=emmeans(mod,~Species)
report.lsmeans(raw.lsm)

# You can display the Statistics in columns

report.lsmeans(raw.lsm,transpose=TRUE)

# In case of just one intercept 

mod=glm(Species~1,data=iris,family=binomial)
raw.lsm=emmeans(mod,~1)
report.lsmeans(raw.lsm)

# Display statistics in columns

report.lsmeans(raw.lsm,transpose=TRUE)


#Mixed model example using lme4

mod=lmer(y_numeric~GROUP+TIMEPOINT+GROUP*TIMEPOINT+(1|SUBJID),data=datafake) 
raw.lsm=emmeans(mod,~GROUP|TIMEPOINT)
report.lsmeans(lsm=raw.lsm,at="TIMEPOINT")

# Display statistics in columns

report.lsmeans(lsm=raw.lsm,at="TIMEPOINT",transpose=TRUE)


# LM model with specific contrast

warp.lm <- lm(breaks ~ wool+tension+wool:tension, data = warpbreaks)
warp.emm <- emmeans(warp.lm, ~ tension | wool)
contr=contrast(warp.emm, "trt.vs.ctrl", ref = "M")
report.lsmeans(lsm=contr,at="wool")


# Display statistics in columns

report.lsmeans(lsm=contr,at="wool",transpose=TRUE)


# Cox model

library(survival)

data(time_to_cure)

fit <- coxph(Surv(time, status) ~ Group, data = time_to_cure) 
em=emmeans(fit,~Group,type="response")
pairs=pairs(em,adjust="none",exclude="Untreated")
pairs

report.lsmeans(pairs)

# Display statistics in columns

report.lsmeans(pairs,transpose=TRUE)

jfrancoiscollin/ClinReport documentation built on Sept. 20, 2020, 7:33 a.m.