biostats_apps: Biostats apps

In biostats-r/biostats.tutorials: Apps and tutorials for statistics and data handling in R

Biostats apps

Description

Shiny apps developed by BioStats

Usage

f_test_app()

influence_leverage_app()

power_lm_app()

publication_bias_app()

t_test_app()

Details

Distributions

• Coming here soon!

Tests

• t_test_app() shows how the t-distribution is used to test the significance of a test result

• f_test_app() shows how the F-distribution is used to test the significance of a test result

Linear models

• influence_leverage_app() explores the impact of outliers, influential, and leverage points on diagnostic plots for linear models. Click the graph to move the red point and refit the model.

Power tests and publication biases

• publication_bias_app() explores the impact of publication bias on the apparent strength of the evidence in the published literature.

• power_lm_app() runs a power test for a linear model with either a continuous or categorical predictor.

Functions

• f_test_app(): f-test and f-distribution

• influence_leverage_app(): Diagnostic plots of models with outliers, leverage points and influential points

• power_lm_app(): Simulate a power test

• publication_bias_app(): Simulation of the effect of publication bias

• t_test_app(): t-tests and t-distribution

biostats-r/biostats.tutorials documentation built on Aug. 27, 2024, 5:05 p.m.