ANOVA table from a linear model fit to data.

Source: R/simple_anova.R

One of two functions for simple ANOVA tables and linear models without random effects, which use lm to fit a linear models.

  1. link{simple_anova}

  2. link{simple_model}

simple_anova(data, Y_value, Fixed_Factor, ...)

Arguments

data

a data table object, e.g. data.frame or tibble.

Y_value

name of column containing quantitative (dependent) variable, provided within "quotes".

Fixed_Factor

name(s) of categorical fixed factors (independent variables) provided as a vector if more than one or within "quotes".

...

any additional argument to pass on to lm if required.

Value

ANOVA table of class "anova" and "data.frame".

Details

Update in v0.2.1: This function uses lm to fit a linear model to data, passes it on to Anova, and outputs the ANOVA table with type II sum of squares with F statistics and P values. (Previous versions produced type I sum of squares using anova call.)

It requires a data table, one quantitative dependent variable and one or more independent variables. If your experiment design has random factors, use the related function mixed_anova.

This function is related to link{simple_model}.

Examples

#Basic usage 
simple_anova(data = data_doubling_time, 
Y_value = "Doubling_time", 
Fixed_Factor = "Student")
#> Anova Table (Type II tests)
#> 
#> Response: Doubling_time
#>           Sum Sq Mean sq Df F value Pr(>F)
#> Student   16.824  1.8694  9  0.4725 0.8761
#> Residuals 79.126  3.9563 20