View source: R/significancetest.R
SignificanceTest | R Documentation |
Standardize information to be shown in significance test results.
SignificanceTest(
obj,
test.name,
vars = NULL,
filter = NULL,
weight = NULL,
p.value.method = "",
show.labels = TRUE,
decimal.places = NULL,
missing = "Exclude cases with missing data",
reg.name = NULL,
reg.sample.description = NULL,
resample = FALSE,
group.levels = NULL
)
obj |
Significance testing output object, e.g. object of class htest. |
test.name |
Name of the test. |
vars |
Variables used in test. |
filter |
Filter variable. |
weight |
Weight variable. |
p.value.method |
Specifies how the p-value is computed. |
show.labels |
Whether to show variable labels instead of names. |
decimal.places |
The number of decimal places to show. |
missing |
How missing data is to be treated in the analysis.
Options are: |
reg.name |
The name of the regression object on which the test is run. |
reg.sample.description |
The sample description of the regression object on which the test is run. |
resample |
Whether resampling is used whenever weights are applied. |
group.levels |
The levels of the categorical group variable. |
This function was created for the following Standard R pages:
Missing Data - Little's MCAR Test
Regression - Diagnostic - Heteroscedasticity
Regression - Diagnostic - Normality (Shapiro-Wilk)
Regression - Diagnostic - Serial Correlation (Durbin-Watson)
Test - Bartlett Test of Sphericity
Test - Chi-Square Test of Independence
Test - Correlation
Test - Nonparametric - Kruskal-Wallis Rank Sum Test
Test - Nonparametric - Paired Samples Wilcoxon Test
Test - Nonparametric - Single-Sample Wilcoxon Test
Test - Nonparametric - Two-Sample Wilcoxon Rank Sum Test
Test - Variance - F-Test to Compare Two Variances
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.