seq_ttest | R Documentation |
Performs one and two sample sequential t-tests on vectors of data. For more information on the sequential t-test, see Schnuerch & Erdfelder (2019) doi:10.1037/met0000234.
seq_ttest(
x,
y = NULL,
data = NULL,
mu = 0,
d,
alpha = 0.05,
power = 0.95,
alternative = "two.sided",
paired = FALSE,
na.rm = TRUE,
verbose = TRUE
)
x |
Works with two classes:
|
y |
an optional (non-empty) numeric vector of data values. |
data |
an optional |
mu |
a number indicating the true value of the mean (or difference in means if you are performing a two sample test). |
d |
a number indicating the specified effect size (Cohen's d) |
alpha |
the type I error. A number between 0 and 1. |
power |
1 - beta (beta is the type II error probability). A number between 0 and 1. |
alternative |
a character string specifying the alternative hypothesis,
must be one of |
paired |
a logical indicating whether you want a paired t-test. |
na.rm |
a logical value indicating whether |
verbose |
a logical value whether you want a verbose output or not. |
An object of the S4 class seq_ttest_results
. Click on the
class link to see the full description of the slots.
To get access to the object use the
@
-operator or []
-brackets instead of $
.
See the examples below.
# set seed --------------------------------------------------------------------
set.seed(333)
# load library ----------------------------------------------------------------
library(sprtt)
# one sample: numeric input ---------------------------------------------------
treatment_group <- rnorm(20, mean = 0, sd = 1)
results <- seq_ttest(treatment_group, mu = 1, d = 0.8)
# get access to the slots -----------------------------------------------------
# @ Operator
results@likelihood_ratio
# [] Operator
results["likelihood_ratio"]
# two sample: numeric input----------------------------------------------------
treatment_group <- stats::rnorm(20, mean = 0, sd = 1)
control_group <- stats::rnorm(20, mean = 1, sd = 1)
seq_ttest(treatment_group, control_group, d = 0.8)
# two sample: formula input ---------------------------------------------------
stress_level <- stats::rnorm(20, mean = 0, sd = 1)
sex <- as.factor(c(rep(1, 10), rep(2, 10)))
seq_ttest(stress_level ~ sex, d = 0.8)
# NA in the data --------------------------------------------------------------
stress_level <- c(NA, stats::rnorm(20, mean = 0, sd = 2), NA)
sex <- as.factor(c(rep(1, 11), rep(2, 11)))
seq_ttest(stress_level ~ sex, d = 0.8, na.rm = TRUE)
# work with dataset (data are in the package included) ------------------------
seq_ttest(monthly_income ~ sex, data = df_income, d = 0.8)
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