likelihoodR (version 1.1.5)

L_t_test_sample_size: Sample size calculation using the evidential approach for t tests

Description

This function calculates the required sample size for t tests. The standard deviation and effect size are specified. Calculations given for one sample and independent samples t tests. For a related samples test calculation use the sd for paired differences.

Usage

L_t_test_sample_size(MW = 0.05, sd = 1, d = 1.2, S = 3, paired = FALSE, verb=TRUE)

Value

$N - required sample size.

$S - specified strength (support) for evidence from the test.

$sd - specified standard deviation.

$d - Cohen's effect size specified.

$m1.w1 - specified probability for combined misleading and weak evidence.

Arguments

MW

set M1 + W1 probability, default = .05.

sd

set standard deviation, default = 1.

d

set desired effect size, default = 1.2.

S

set strength of evidence (support), default = 3.

paired

set to TRUE for one sample and FALSE for independent samples, default = FALSE.

verb

show output, default = TRUE.

References

Cahusac, P.M.B. (2020) Evidence-Based Statistics, Wiley, ISBN : 978-1119549802

Cahusac, P.M.B. & Mansour, S.E. (2022) Estimating sample sizes for evidential t tests, Research in Mathematics, 9(1):1-12 https://doi.org/10.1080/27684830.2022.2089373

Royall, R. (2000). "On the Probability of Observing Misleading Statistical Evidence." Journal of the American Statistical Association 95(451): 760.

Royall, R. (2004). The Likelihood paradigm for statistical evidence. The Nature of Scientific Evidence. M. L. Taper and S. R. Lele. Chicago, University of Chicago: 119.

Royall, R. M. (1997). Statistical evidence: A likelihood paradigm. London: Chapman & Hall, ISBN : 978-0412044113

Edwards, A.W.F. (1992) Likelihood, Johns Hopkins Press, ISBN : 978-0801844430

Examples

# for one sample or related samples (differences)
v = L_t_test_sample_size(MW = 0.2, sd = 1, d = 1, S = 3, paired = TRUE)
v
# for 2 independent samples
v = L_t_test_sample_size(MW = 0.05, sd = 1, d = 1.2, S = 3, paired = FALSE)
v