ttest {rigr}

T-test with Improved Layout

Description

Performs a one- or two-sample t-test using data. In the two-sample case, the user can specify whether or not observations are matched, and whether or not equal variances should be presumed.

Usage

ttest(
  var1,
  var2 = NA,
  by = NA,
  geom = FALSE,
  null.hypoth = 0,
  alternative = "two.sided",
  var.eq = FALSE,
  conf.level = 0.95,
  matched = FALSE,
  more.digits = 0
)

Arguments

var1

a (non-empty) numeric vector of data values.

var2

an optional (non-empty) numeric vector of data.

by

a variable of equal length to that of var1 with two outcomes. This will be used to define strata for a t-test on var1.

geom

a logical indicating whether the geometric mean should be calculated and displayed.

null.hypoth

a number specifying the null hypothesis for the mean (or difference in means if performing a two-sample test). Defaults to zero.

alternative

a string: one of "less", "two.sided", or "greater" specifying the form of the test. Defaults to a two-sided test.

var.eq

a logical value, either TRUE or FALSE (default), specifying whether or not equal variances should be presumed in a two-sample t-test. Also controls robust standard errors.

conf.level

confidence level of the test. Defaults to 0.95.

matched

a logical value, either TRUE or FALSE, indicating whether or not the variables of a two-sample t-test are matched. Variables must be of equal length.

more.digits

a numeric value specifying whether or not to display more or fewer digits in the output. Non-integers are automatically rounded down.

Details

Missing values must be given by NA to be recognized as missing values.

Value

a list of class ttest. The print method lays out the information in an easy-to-read format.

tab

A formatted table of descriptive and inferential statistics (total number of observations, number of missing observations, mean, standard error of the mean estimate, standard deviation), along with a confidence interval for the mean.

df

Degrees of freedom for the t-test.

p

P-value for the t-test.

tstat

Test statistic for the t-test.

var1

The user-supplied first data vector.

var2

The user-supplied second data vector.

by

The user-supplied stratification variable.

par

A vector of information about the type of test (null hypothesis, alternative hypothesis, etc.)

geo

A formatted table of descriptive and inferential statistics for the geometric mean.

call

The call made to the ttest function.

See Also

t.test

Examples

# Read in data set
data(psa)
attach(psa)

# Perform t-test
ttest(pretxpsa, null.hypoth = 100, alternative = "greater", more.digits = 1)

# Define new binary variable as indicator
# of whether or not bss was worst possible
bssworst <- bss
bssworst[bss == 1] <- 0
bssworst[bss == 2] <- 0
bssworst[bss == 3] <- 1

# Perform t-test allowing for unequal
# variances between strata -#
ttest(pretxpsa, by = bssworst)

# Perform matched t-test
ttest(pretxpsa, nadirpsa, matched = TRUE, conf.level = 99/100, more.digits = 1)