RandomizedBlocksAnalysis function

RandomizedBlocksAnalysis

RandomizedBlocksAnalysis

The function performs a heteroscedastic test of a two treatment by J blocks randomized blocks effect size. The data are assumed to be stored in xx in list mode. All groups are assumed to be independent. Missing values are not permitted.

RandomizedBlocksAnalysis( x, con = c(-0.5, 0.5, -0.5, 0.5), alpha = 0.05, alternative = "two.sided" )

Arguments

  • x: the structure holding the data. In list format, for a 2 treatment by J block randomized blocks experiments, there are 2J list elements each one specifying the outcome for a specific block and a specific treatment.
  • con: is a 2J list containing the contrast coefficients that are used to calculate the mean effect size.
  • alpha: is the Type 1 error level used for the test of significance (default 0.05)
  • alternative: The type of statistical test. Valid values are one of c('two.sided', 'greater', 'less')

Returns

The t-test and its associated metrics (i.e., critical value standard error and degrees of freedom) and the estimate of the contrast with its upper and lower confidence interval bounds and p-value.

Examples

set.seed(123) x <- list() x[[1]] <- rnorm(10, 0, 1) x[[2]] <- rnorm(10, 0.8, 1) x[[3]] <- rnorm(10, 0.5, 1) x[[4]] <- rnorm(10, 1.3, 1) vec <- c(-1, 1, -1, 1) / 2 RandomizedBlocksAnalysis(x, con = vec, alpha = 0.05) # $n # [1] 10 10 10 10 # $test # test crit se df # [1,] 4.432644 2.038622 0.2798104 31.33793 # $psihat # psihat ci.lower ci.upper p.value # [1,] 1.2403 0.6698721 1.810728 0.0001062952 # $sig # [1] TRUE RandomizedBlocksAnalysis(x,con=vec,alpha=0.05,alternative='greater') # n # [1] 10 10 10 10 # $test # test crit se df # [1,] 4.432644 1.694956 0.2798104 31.33793 # $psihat # psihat ci.lower ci.upper p.value #[1,] 1.2403 0.7660336 Inf 5.314762e-05 # $sig # [1] TRUE RandomizedBlocksAnalysis(x,con=-vec,alpha=0.05,alternative='greater') #$n #[1] 10 10 10 10 #$test # test crit se df #[1,] -4.432644 1.694956 0.2798104 31.33793 #$psihat # psihat ci.lower ci.upper p.value #[1,] -1.2403 -1.714566 Inf 0.9999469 #$sig #[1] FALSE x[[5]]=rnorm(10,-0.2,1) x[[6]]=rnorm(10,0.6,1) vec=c(1,-1,1,-1,1,-1)/3 RandomizedBlocksAnalysis(x,con=vec,alpha=0.05,alternative='less') #$n #[1] 10 10 10 10 10 10 #$test # test crit se df #[1,] -4.946987 1.677021 0.236575 48.29776 #$psihat # psihat ci.lower ci.upper p.value #[1,] -1.170334 -Inf -0.7735925 4.76961e-06 #$sig #[1] TRUE

Author(s)

Barbara Kitchenham and Lech Madeyski