t-test contrasts for one-way repeated measures

t-test contrasts for one-way repeated measures

t_contrast_rm(df, subject, dv, condition, A_levels, B_levels,
  contrast_weights, report = TRUE)

Arguments

df	A long format dataframe
subject	name of the subject column
dv	name of the dependent variable column
condition	name of the condition for the one-way manipulation
A_levels	character vector, including the names of the levels for the first side of the contrast
B_levels	character vector, including the names of the levels for the second side of the contrast
contrast_weights	numeric vector, including the contrast weights for all levels, in the same order as they are listed in A and B levels
report	logical, TRUE = the t.test summary will print out even if you assign the object to a variable, FALSE = no extra printing

Value

t.test summary

Examples

some_data <- data.frame(s = rep(1:10,3),
                       measure = rnorm(30,0,1),
                       manipulation = as.factor(rep(c("A","B","C"),each=10)))
t_contrast_rm(df = some_data,
              subject = "s",
              dv = "measure",
              condition = "manipulation",
              A_levels = c("A"),
              B_levels = c("B","C"),
              contrast_weights = c(-1,.5,.5))
#> 
#> 	One Sample t-test
#> 
#> data:  contrast_vector
#> t = 0.68467, df = 9, p-value = 0.5108
#> alternative hypothesis: true mean is not equal to 0
#> 95 percent confidence interval:
#>  -0.6687136  1.2491879
#> sample estimates:
#> mean of x 
#> 0.2902371 
#> 
#> 
#> 	One Sample t-test
#> 
#> data:  contrast_vector
#> t = 0.68467, df = 9, p-value = 0.5108
#> alternative hypothesis: true mean is not equal to 0
#> 95 percent confidence interval:
#>  -0.6687136  1.2491879
#> sample estimates:
#> mean of x 
#> 0.2902371 
#>