Learn R Programming

misty (version 0.4.6)

test.t: t-Test

Description

This function performs one-sample, two-sample, and paired-sample t-tests and provides descriptive statistics, effect size measure, and a plot showing error bars for confidence intervals with jittered data points.

Usage

test.t(x, ...)

# S3 method for default test.t(x, y = NULL, mu = 0, paired = FALSE, alternative = c("two.sided", "less", "greater"), conf.level = 0.95, hypo = TRUE, descript = TRUE, effsize = FALSE, weighted = TRUE, cor = TRUE, ref = NULL, correct = FALSE, plot = FALSE, point.size = 4, error.width = 0.1, xlab = NULL, ylab = NULL, ylim = NULL, breaks = ggplot2::waiver(), line = TRUE, line.type = 3, line.size = 0.8, jitter = TRUE, jitter.size = 1.25, jitter.width = 0.05, jitter.alpha = 0.1, title = "", subtitle = "Confidence Interval", digits = 2, p.digits = 4, as.na = NULL, check = TRUE, output = TRUE, ...)

# S3 method for formula test.t(formula, data, alternative = c("two.sided", "less", "greater"), conf.level = 0.95, hypo = TRUE, descript = TRUE, effsize = FALSE, weighted = TRUE, cor = TRUE, ref = NULL, correct = FALSE, plot = FALSE, point.size = 4, error.width = 0.1, xlab = NULL, ylab = NULL, ylim = NULL, breaks = ggplot2::waiver(), jitter = TRUE, jitter.size = 1.25, jitter.width = 0.05, jitter.alpha = 0.1, title = "", subtitle = "Confidence Interval", digits = 2, p.digits = 4, as.na = NULL, check = TRUE, output = TRUE, ...)

Value

Returns an object of class misty.object, which is a list with following entries: function call (call), type of analysis type, list with the input specified in x and y (data), data used to plot the results (plot.data), specification of function arguments (args), and result table (result).

Arguments

x

a numeric vector of data values.

y

a numeric vector of data values.

mu

a numeric value indicating the population mean under the null hypothesis. Note that the argument mu is only used when computing a one sample t-test.

paired

logical: if TRUE, paired-samples t-test is computed.

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".

hypo

logical: if TRUE, null and alternative hypothesis are shown on the console.

descript

logical: if TRUE, descriptive statistics are shown on the console.

effsize

logical: if TRUE, effect size measure Cohen's d is shown on the console, see cohens.d function.

weighted

logical: if TRUE (default), the weighted pooled standard deviation is used to compute Cohen's d for a two-sample design (i.e., paired = FALSE), while standard deviation of the difference scores is used to compute Cohen's d for a paired-sample design (i.e., paired = TRUE).

cor

logical: if TRUE (default), paired = TRUE, and weighted = FALSE, Cohen's d for a paired-sample design while controlling for the correlation between the two sets of measurement is computed. Note that this argument is only used in a paired-sample design (i.e., paired = TRUE) when specifying weighted = FALSE.

ref

character string "x" or "y" for specifying the reference reference group when using the default test.t() function or a numeric value or character string indicating the reference group in a two-sample design when using the formula test.t() function. The standard deviation of the reference variable or reference group is used to standardized the mean difference to compute Cohen's d. Note that this argument is only used in a two-sample design (i.e., paired = FALSE).

correct

logical: if TRUE, correction factor to remove positive bias in small samples is used.

conf.level

a numeric value between 0 and 1 indicating the confidence level of the interval.

plot

logical: if TRUE, a plot showing error bars for confidence intervals is drawn.

point.size

a numeric value indicating the size aesthetic for the point representing the mean value.

error.width

a numeric value indicating the horizontal bar width of the error bar.

xlab

a character string specifying the labels for the x-axis.

ylab

a character string specifying the labels for the y-axis.

ylim

a numeric vector of length two specifying limits of the limits of the y-axis.

breaks

a numeric vector specifying the points at which tick-marks are drawn at the y-axis.

line

logical: if TRUE (default), a horizontal line is drawn at mu for the one-sample t-test or at 0 for the paired-sample t-test.

line.type

an integer value or character string specifying the line type for the line representing the population mean under the null hypothesis, i.e., 0 = blank, 1 = solid, 2 = dashed, 3 = dotted, 4 = dotdash, 5 = longdash, 6 = twodash.

line.size

a numeric value indicating the size aesthetic for the line representing the population mean under the null hypothesis.

jitter

logical: if TRUE (default), jittered data points are drawn.

jitter.size

a numeric value indicating the size aesthetic for the jittered data points.

jitter.width

a numeric value indicating the amount of vertical and horizontal jitter.

jitter.alpha

a numeric value indicating the opacity of the jittered data points.

title

a character string specifying the text for the title for the plot.

subtitle

a character string specifying the text for the subtitle for the plot.

digits

an integer value indicating the number of decimal places to be used for displaying descriptive statistics and confidence interval.

p.digits

an integer value indicating the number of decimal places to be used for displaying the p-value.

as.na

a numeric vector indicating user-defined missing values, i.e. these values are converted to NA before conducting the analysis.

check

logical: if TRUE, argument specification is checked.

output

logical: if TRUE, output is shown on the console.

formula

in case of two sample t-test (i.e., paired = FALSE), a formula of the form y ~ group where group is a numeric variable, character variable or factor with two values or factor levels giving the corresponding groups.

data

a matrix or data frame containing the variables in the formula formula.

...

further arguments to be passed to or from methods.

Author

Takuya Yanagida takuya.yanagida@univie.ac.at

References

Rasch, D., Kubinger, K. D., & Yanagida, T. (2011). Statistics in psychology - Using R and SPSS. John Wiley & Sons.

See Also

aov.b, test.welch, test.z, test.levene, cohens.d, ci.mean.diff, ci.mean