Counternull (version 0.2.12)

create_null_rand: Create Null Randomization Distribution

Description

Generates null randomization distribution for a given test statistic.

Usage

create_null_rand(
  y,
  w,
  rand_matrix,
  test_stat = NULL,
  fun = NULL,
  alternative = NULL,
  bw = NULL
)

Value

Class "null_rand" with 11 entries:

null_dist

Vector of permuted test statistics under the null hypothesis

t_obs

Observed test statistic

counts

Number of test statistics more extreme than observed test statistic

pvalue

Fisher-Exact P-value

alternative

Specified alternative

rand_matrix

Randomization matrix used to generate null distribution

bin_width

Specified bin width

y

Observed outcomes

w

Vector indicating treatment assignments

test_stat

Name of built in test statistic function

fun

Test statistic function

Arguments

y

Vector of observed outcomes

w

Vector indicating treatment assignments

rand_matrix

Matrix with permutations for experiment assignments

test_stat

Name of built in test statistic function. Provide "diffmeans" for difference of means, "t" for t test, "paired-t" for paired t test, and "cohens-d" for cohen's d test (optional).

fun

Test statistic function (optional).

alternative

Character string specifying alternative hypothesis. Must be one of "two-sided" (default), "greater", or "less".

bw

Bin width for histogram (optional)

Details

Call summary on "null_rand" class to retrieve information on the null randomization distribution. Call plot on "null_rand" class for visualization of null randomization distribution.

Assignments must be indicated in arguments "w" and "rand_matrix" using numeric 1 or 0.

Argument "rand_matrix" must have assignment permutations in each column and must have the same number of rows as there are entries in "w".

One of either argument "test_stat" or "fun" must be specified.

Argument "fun" must take in two parameters (treated outcomes and control outcomes) and returns a numeric test statistic value (scalar).

Examples

y = sample_data$turn_angle
w = sample_data$w
n_r = create_null_rand(y, w, sample_matrix, test_stat = c("t"))
summary(n_r)
plot(n_r)