print.summary.normality_test

Displays the SPSS-style "Tests of Normality" table (Kolmogorov-Smirnov
with Lilliefors correction, Shapiro-Wilk) for a
<code>normality_test</code> result, per group for grouped data.

Statistical analysis of survey data with full support
for survey weights, grouped operations, and 'tidyverse' integration. Provides
80 functions for data import/export ('SPSS', 'Stata', 'SAS', 'Excel') with
label roundtripping and tagged NA preservation, label management (variable
labels, value labels, type conversions, missing value declaration), data
transformation (recoding, dummy coding, standardization, centering),
descriptive statistics, codebook generation, hypothesis testing, correlation
analysis, post-hoc comparisons, weighted statistics, scale analysis,
regression, non-parametric tests, exact tests, factorial ANOVA, and ANCOVA.
Every analysis offers compact print() and detailed summary() output with
toggleable sections. Statistical results are validated against 'SPSS'
version 29 within documented per-tier tolerances (see the compatibility
vignette for per-function status). Methods follow the published
algorithms of IBM Corp. (2023, "IBM SPSS Statistics Algorithms"),
the Lilliefors-corrected normality test of Dallal and Wilkinson
(1986) <doi:10.1080/00031305.1986.10475419>, and the adjusted
standardized residuals of Haberman (1973) <doi:10.2307/2529686>.
Designed for survey researchers, social scientists, and students
working with complex survey designs.

Yannick Diehl

mariposa

'SPSS'-Compatible Statistical Tools for Survey Data

print.summary.normality_test function

<dl><dt>x</dt>
<dd>A <code>summary.normality_test</code> object created by
<code>summary.normality_test</code>.</dd>
<dt>...</dt>
<dd>Additional arguments (not used).</dd></dl>

Arguments

Print summary of normality test results (detailed output) — print.summary.normality_test

<dl>

<dt>x</dt>
<dd>A <code>summary.normality_test</code> object created by
<code>summary.normality_test</code>.</dd>


<dt>...</dt>
<dd>Additional arguments (not used).</dd>

</dl>

print.summary.normality_test: Print summary of normality test results (detailed output)

Description

Usage

Value

Arguments

See Also

Examples