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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