T-test Given Summary Statistics with Improved Layout

Performs a one- or two-sample t-test given summary statistics. In the two-sample case, the user can specify whether or not equal variances should be presumed.

Usage

ttesti(
  obs,
  mean,
  sd,
  obs2 = NA,
  mean2 = NA,
  sd2 = NA,
  null.hypoth = 0,
  conf.level = 0.95,
  alternative = "two.sided",
  var.eq = FALSE,
  more.digits = 0
)

Arguments

obs: number of observations for the first sample.
mean: the sample mean of the first sample.
sd: the sample standard deviation of the first sample.
obs2: number of observations for the second sample (this is optional).
mean2: if obs2 is supplied, then sample mean of the second sample must be supplied.
sd2: if obs2 is supplied, then sample standard deviation of the second sample must be supplied.
null.hypoth: a number specifying the null hypothesis for the mean (or difference in means if performing a two-sample test). Defaults to zero.
conf.level: confidence level of the test. Defaults to 0.95.
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.
more.digits: a numeric value specifying whether or not to display more or fewer digits in the output. Non-integers are automatically rounded down.

Value

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

tab: A formatted table of descriptive and inferential statistics (number of 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.
par: A vector of information about the type of test (null hypothesis, alternative hypothesis, etc.)
twosamp: A logical value indicating whether a two-sample test was performed.
call: The call made to the ttesti function.

Details

If obs2, mean2, or sd2 is specified, then all three must be specified and a two-sample t-test is run.

Examples


# t-test given sample descriptives
ttesti(24, 175, 35, null.hypoth=230)
#> 
#> Call:
#> ttesti(obs = 24, mean = 175, sd = 35, null.hypoth = 230)
#> 
#> One-sample t-test :
#>  
#> Summary:
#>      Obs Mean Std. Error Std. Dev. 95% CI    
#> var1 24  175  7.14       35        [160, 190]
#> 
#>  Ho:  mean = 230 ; 
#>  Ha:  mean != 230 
#>  t = -7.698 , df = 23 
#>  Pr(|T| > t) =  8.23997e-08 

# two-sample test
ttesti(10, -1.6, 1.5, 30, -.7, 2.1)
#> 
#> Call:
#> ttesti(obs = 10, mean = -1.6, sd = 1.5, obs2 = 30, mean2 = -0.7, 
#>     sd2 = 2.1)
#> 
#> Two-sample t-test allowing for unequal variances :
#>  
#> Summary:
#>      Obs Mean Std. Error Std. Dev. 95% CI         
#> var1 10  -1.6 0.474      1.5       [-2.67, -0.527]
#> var2 30  -0.7 0.383      2.1       [-1.48, 0.0842]
#> diff 40  -0.9 0.61       <NA>      [-2.13, 0.335] 
#> 
#>  Ho: difference in  means = 0 ; 
#>  Ha: difference in  means != 0 
#>  t = -1.476 , df = 21.7239 
#>  Pr(|T| > t) =  0.154397