View source: R/work_test_norm_local.R
adaptive_analysis_norm_local | R Documentation |
adaptive_analysis_norm_local
performs an locally efficient adaptive test,
a Frequentist adaptive test with the specified significance level
with full flexibility.
Normality with known variance is assumed for the test statistic
(more accurately, the test statistic is assumed to follow Brownian motion.)
Null hypothesis is fixed at 0 without loss of generality.
No procedure to calculate p-value or confidence intervals is employed.
For detailed illustration, see vignette("adpss_ex")
.
adaptive_analysis_norm_local( overall_sig_level = 0.025, min_effect_size = 1, times = 0, stats = 0, final_analysis = TRUE, estimate = FALSE, ci_coef = 0.95, input_check = TRUE )
overall_sig_level |
Overall significance level in (0, 1). Default is 0.025. |
min_effect_size |
The minimum effect size. It should be positive. The working test will be constructed to have the power of |
times |
The sequence of times (sample size or information level) at which analyses were conducted. |
stats |
The sequence of test statistics. |
final_analysis |
If |
estimate |
If |
ci_coef |
The confidence coefficient. Default is 0.95. |
input_check |
Indicate whether or not the arguments input by user contain invalid values. |
List of results including the conditional Type I error probability.
Kashiwabara, K., Matsuyama, Y. An efficient adaptive design approximating fixed sample size designs. In preparation.
sample_size_norm_local
.
# Sample size calculation sample_size_norm_local( overall_sig_level = 0.025, min_effect_size = -log(0.65), effect_size = 11.11 / 20.02, # needs not be MLE time = 20.02, target_power = 0.75, sample_size = TRUE )
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