BFpower.cor: Sample size determination for Bayesian correlation test

Description

Perform sample size determination or the calculation of compelling and misleading evidence for a Bayesian correlation test.

Usage

BFpower.cor(
  hypothesis = NULL,
  h0 = NULL,
  e = NULL,
  interval = NULL,
  D = NULL,
  target = NULL,
  FP = NULL,
  model = NULL,
  k = NULL,
  alpha = NULL,
  beta = NULL,
  scale = NULL,
  model_d = NULL,
  alpha_d = NULL,
  beta_d = NULL,
  location_d = NULL,
  k_d = NULL,
  scale_d = NULL,
  de_an_prior = NULL,
  N = NULL,
  mode_bf = NULL,
  direct = NULL
)

Value

A data frame with the following columns:

p(BF10 > D | H1): Probability of obtaining compelling evidence in favor of the alternative hypothesis when the alternative is true.
p(BF01 > D | H1): Probability of obtaining misleading evidence in favor of the null hypothesis when the alternative is true.
p(BF01 > D | H0): Probability of obtaining compelling evidence in favor of the null hypothesis when the null is true.
p(BF10 > D | H0): Probability of obtaining misleading evidence in favor of the alternative hypothesis when the null is true.
Required N: The required sample size or the sample size input by the users.

If sample size determination fails, the function returns NULL.

Arguments

hypothesis: The hypothesis being tested (e.g., two-sided "!=", right-sided ">", left-sided "<").
h0: Null value of the correlation.
e: The bounds for the interval Bayes factor (used when interval = 0).
interval: Character or integer (0 or 1). If "1", Bayes factor with a point null against a composite alternative hypothesis; otherwise Bayes factor with interval null and alternative hypotheses.
D: The bound of compelling evidence.
target: The targeted true positive rate (if direct = "h1") or true negative rate (if direct = "h0").
FP: The targeted false positive rate (if direct = "h1") or false negative rate (if direct = "h0").
model: Statistical model of the analysis prior under the alternative hypothesis: default beta ("d_beta"), beta ("beta"), or normal moment ("NLP")
k: Parameter for the analysis default beta prior under the alternative hypothesis.
alpha: Parameter for the analysis beta prior under the alternative hypothesis.
beta: Parameter for the analysis beta prior under the alternative hypothesis.
scale: Scale parameter for the analysis normal moment prior under the alternative hypothesis.
model_d: Statistical model of the design prior under the alternative hypothesis:default beta ("d_beta"), beta ("beta"), normal moment ("NLP" , or point "Point")
alpha_d: Parameter for the design beta prior under the alternative hypothesis.
beta_d: Parameter for the design beta prior under the alternative hypothesis.
location_d: Location parameter for the design point prior under the alternative hypothesis.
k_d: Parameter for the design default beta prior under the alternative hypothesis.
scale_d: Scale parameter for the design normal moment prior under the alternative hypothesis.
de_an_prior: Integer (0 or 1). If 1, analysis and design priors under the alternative are the same; if 0, they are not.
N: Sample size.
mode_bf: Integer (0 or 1). If 1, sample size determination; if 2, N is needed for the calculation of probabilities of compelling and misleading evidence.
direct: If "h1", BF10; if "h0", BF01.

Examples

Run this code

BFpower.cor(
  hypothesis = "!=",
  h0 = 0,
  e = NULL,
  interval = "1",
  D = 3,
  target = 0.8,
  FP = 0.05,
  model = "d_beta",
  k = 1,
  de_an_prior = 1,
  mode_bf = 1,
  direct = "h1"
)

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