View source: R/L_t_test_sample_size.R
L_t_test_sample_size | R Documentation |
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.
L_t_test_sample_size(MW = 0.05, sd = 1, d = 1.2, S = 3, paired = FALSE, verb=TRUE)
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. |
$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.
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
# 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
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