tab (version 1.0)

tabmeans: Generate summary tables of mean comparisons for statistical reports.

Description

This function compares the mean of a continuous variable across levels of a factor variable and summarizes the results in a clean table for a statistical report.

Usage

tabmeans(x, y, xlevels=NULL, yname="Y variable", decimals=1, n=TRUE, se=FALSE)

Arguments

x

Vector of values for the factor variable.

y

Vector of values for the continuous variable.

xlevels

Optional character vector to label the levels of x. If unspecified, the function uses generic labels.

yname

Optional label for the continuous varaible.

decimals

Number of decimal places for means and standard deviations or standard errors.

n

If TRUE, the table returned will include sample sizes in the column headings.

se

If TRUE, the table will present mean (standard error) rather than mean (standard deviation).

Value

• A character matrix with the requested frequency table. If you click on the matrix name under "Data" in the RStudio Workspace tab, you will see a clean table that you can copy and paste into a statistical report or manuscript.

Details

If x has two levels, a t-test is used to test for a difference in means. An F test is first used to determine whether the equal variance or unequal variance t-test is appropriate. If x has more than two levels, a one-way analysis of variance is used to test for a difference in means across the groups.

References

Acknowledgment: This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-0940903.

See Also

tabfreq tablin tablog tabcox

Examples

# Load in example dataset d
data(d)

# Create labels for group and race
groups = c("Control","Treatment")
races = c("White","Black","Mexican American","Other")

# Compare mean BMI in control group vs. treatment group
meanstable1 = tabmeans(x=d$group,y=d$bmi,xlevels=groups,yname="BMI")

# Compare mean BMI by race and omit sample size
meanstable2 = tabmeans(x=d$race,y=d$bmi,xlevels=races,yname="BMI",n=FALSE)

# Create single table comparing mean BMI and mean age in control vs. treatment group
meanstable3 = rbind(tabmeans(x=d$group,y=d$bmi,xlevels=groups,yname="BMI"),
                    tabmeans(x=d$group,y=d$age,xlevels=groups,yname="Age"))

# Click on meanstable1, meanstable2, and meanstable3 in the Workspace tab of RStudio 
# to see the tables that could be copied and pasted into a report or manuscript.