ttest | R Documentation |
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.
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 )
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 |
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
|
var.eq |
a logical value, either
|
conf.level |
confidence level of the test. Defaults to 0.95. |
matched |
a logical value, either
|
more.digits |
a numeric value specifying whether or not to display more or fewer digits in the output. Non-integers are automatically rounded down. |
Missing values must be given by NA
to be recognized as missing values.
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 |
t.test
# 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)
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