https://github.com/cran/inferr
Tip revision: 59444f93bc0b45cd4ab2cf3493acf201d9fdc5b9 authored by Aravind Hebbali on 28 May 2021, 16:30:02 UTC
version 0.3.1
version 0.3.1
Tip revision: 59444f9
README.md
<!-- README.md is generated from README.Rmd. Please edit that file -->
# inferr
> Tools for Statistical Inference
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## Overview
inferr builds upon the statistical tests provided in **stats**, provides
additional and flexible input options and more detailed and structured
test results. As of version 0.3, **inferr** includes a select set of
parametric and non-parametric statistical tests which are listed below:
- One Sample t Test
- Paired Sample t Test
- Independent Sample t Test
- One Sample Proportion Test
- Two Sample Proportion Test
- One Sample Variance Test
- Two Sample Variance Test
- Binomial Test
- ANOVA
- Chi Square Goodness of Fit Test
- Chi Square Independence Test
- Levene’s Test
- Cochran’s Q Test
- McNemar Test
- Runs Test for Randomness
## Installation
``` r
# install inferr from CRAN
install.packages("inferr")
# the development version from github
# install.packages("devtools")
devtools::install_github("rsquaredacademy/inferr")
```
## Articles
- [Introduction to
inferr](https://inferr.rsquaredacademy.com/articles/intro.html)
## Usage
#### One Sample t Test
``` r
infer_os_t_test(hsb, write, mu = 50, type = 'all')
#> One-Sample Statistics
#> ---------------------------------------------------------------------------------
#> Variable Obs Mean Std. Err. Std. Dev. [95% Conf. Interval]
#> ---------------------------------------------------------------------------------
#> write 200 52.775 0.6702 9.4786 51.4537 54.0969
#> ---------------------------------------------------------------------------------
#>
#> Two Tail Test
#> ---------------
#>
#> Ho: mean(write) ~=50
#> Ha: mean(write) !=50
#> --------------------------------------------------------------------------------
#> Variable t DF Sig Mean Diff. [95% Conf. Interval]
#> --------------------------------------------------------------------------------
#> write 4.141 199 0.00005 2.775 1.4537 4.0969
#> --------------------------------------------------------------------------------
```
#### ANOVA
``` r
infer_oneway_anova(hsb, write, prog)
#> ANOVA
#> ----------------------------------------------------------------------
#> Sum of
#> Squares DF Mean Square F Sig.
#> ----------------------------------------------------------------------
#> Between Groups 3175.698 2 1587.849 21.275 0
#> Within Groups 14703.177 197 74.635
#> Total 17878.875 199
#> ----------------------------------------------------------------------
#>
#> Report
#> -----------------------------------------
#> Category N Mean Std. Dev.
#> -----------------------------------------
#> 1 45 51.333 9.398
#> 2 105 56.257 7.943
#> 3 50 46.760 9.319
#> -----------------------------------------
#>
#> Number of obs = 200 R-squared = 0.1776
#> Root MSE = 8.6392 Adj R-squared = 0.1693
```
#### Chi Square Test of Independence
``` r
infer_chisq_assoc_test(hsb, female, schtyp)
#> Chi Square Statistics
#>
#> Statistics DF Value Prob
#> ----------------------------------------------------
#> Chi-Square 1 0.0470 0.8284
#> Likelihood Ratio Chi-Square 1 0.0471 0.8282
#> Continuity Adj. Chi-Square 1 0.0005 0.9822
#> Mantel-Haenszel Chi-Square 1 0.0468 0.8287
#> Phi Coefficient 0.0153
#> Contingency Coefficient 0.0153
#> Cramer's V 0.0153
#> ----------------------------------------------------
```
#### Levene’s Test
``` r
infer_levene_test(hsb, read, group_var = race)
#> Summary Statistics
#> Levels Frequency Mean Std. Dev
#> -----------------------------------------
#> 1 24 46.67 10.24
#> 2 11 51.91 7.66
#> 3 20 46.8 7.12
#> 4 145 53.92 10.28
#> -----------------------------------------
#> Total 200 52.23 10.25
#> -----------------------------------------
#>
#> Test Statistics
#> -------------------------------------------------------------------------
#> Statistic Num DF Den DF F Pr > F
#> -------------------------------------------------------------------------
#> Brown and Forsythe 3 196 3.44 0.0179
#> Levene 3 196 3.4792 0.017
#> Brown and Forsythe (Trimmed Mean) 3 196 3.3936 0.019
#> -------------------------------------------------------------------------
```
#### Cochran’s Q Test
``` r
infer_cochran_qtest(exam, exam1, exam2, exam3)
#> Test Statistics
#> ----------------------
#> N 15
#> Cochran's Q 4.75
#> df 2
#> p value 0.093
#> ----------------------
```
#### McNemar Test
``` r
hb <- hsb
hb$himath <- ifelse(hsb$math > 60, 1, 0)
hb$hiread <- ifelse(hsb$read > 60, 1, 0)
infer_mcnemar_test(hb, himath, hiread)
#> Controls
#> ---------------------------------
#> Cases 0 1 Total
#> ---------------------------------
#> 0 135 21 156
#> 1 18 26 44
#> ---------------------------------
#> Total 153 47 200
#> ---------------------------------
#>
#> McNemar's Test
#> ----------------------------
#> McNemar's chi2 0.2308
#> DF 1
#> Pr > chi2 0.631
#> Exact Pr >= chi2 0.7493
#> ----------------------------
#>
#> Kappa Coefficient
#> --------------------------------
#> Kappa 0.4454
#> ASE 0.075
#> 95% Lower Conf Limit 0.2984
#> 95% Upper Conf Limit 0.5923
#> --------------------------------
#>
#> Proportion With Factor
#> ----------------------
#> cases 0.78
#> controls 0.765
#> ratio 1.0196
#> odds ratio 1.1667
#> ----------------------
```
## Getting Help
If you encounter a bug, please file a minimal reproducible example using
[reprex](https://reprex.tidyverse.org/index.html) on github. For
questions and clarifications, use
[StackOverflow](https://stackoverflow.com/).
