![]() # The sd in the second group is twice the sd in the second group See errors from it, notably about inability to bracket the root Uniroot is used to solve power equation for unknowns, so you may Object of class power.htest, a list of the arguments (including the computed one) Significance level if the true difference is zero. Of rejection in the opposite direction of the true effect, in the The default strict = TRUE ensures that the power will include the probability So NULL must be explicitly passed if you want to compute them. Notice that the last two have non-NULL defaults Defaults to TRUE unlike the standard power.t.test function.Įxactly one of the parameters n, delta, power, sd, sig.level, ratio sd.ratioĪnd that parameter is determined from the others. Use strict interpretation in two-sided case. Possibilities are welch (the default) or classical. Method for calculating the degrees of default. Defaults to 1 (equal standard deviations in the two groups) The ratio sd2/sd1 between the standard deviations in the larger group and the smaller group. If ratio is set to NULL (i.e., find the ratio) then the ratio might be smaller than 1 depending on the desired power and ratio of the sd's. Should be a value equal to or greater than 1 since n2 is the larger group. The ratio n2/n1 between the larger group and the smaller group. Power of test (1 minus Type II error probability) Significance level (Type I error probability) Number of observations (in the smallest group if two groups) Type = c("two.sample", "one.sample", "paired"),Īlternative = c("two.sided", "one.sided"), Power for equal and unequal sample sizes. Power calculations for one and two sample t tests with unequal sample size DescriptionĬompute power of test, or determine parameters to obtain target pairwise_Schur_product: Compute Schur products (element-wise) of all pairwise.: Pairwise Tests for Association/Correlation Between Paired.pairwise_combination_indices: Compute all pairwise combinations of indices. ![]() ordered.clusters: Check if unique elements of a vector appear in contiguous.monte_carlo_chisq_test: Two-sided table test with fixed margins.mfastLmCpp: Fast marginal simple regresion analyses.MESS: Collection of miscellaneous useful and semi-useful functions.maximum_subarray: Fast computation of maximum sum subarray.: Split Matrix by Clusters and Return Lower Triangular Parts as.loadRData: Load and extract object from RData file.lifeexpect: Estimated life expectancy for Danish newborns.kwdata: Non-parametric Kruskal Wallis data example.ks_cumtest: Kolmogorov-Smirnov goodness of fit test for cumulative.icecreamads: Ice cream consumption and advertising.hwe_frequencies: Fast estimation of allele and genotype frequencies under.ht: Show the head and tail of an object.happiness: Happiness score and tax rates for 148 countries.greenland: Average yearly summer air temperature for Tasiilaq, Greenland.gkgamma: Goodman-Kruskal's gamma statistic for a two-dimensional table.geekin: Fit a generalized estimating equation (GEE) model with fixed.founder.shared: Compute a common shared environment matrix.filldown: Fill down NA with the last observed observation.feature.test: Inference for features identified by the Lasso.fac2num: Convert factor to numeric vector.extended.shared: Compute a common shared environment matrix.expand_table: Expand table or matrix to data frame.drop1.geem: Drop All Possible Single Terms to a geem Model Using Wald or.drop1.geeglm: Drop All Possible Single Terms to a geeglm Model Using Wald.cumsumbinning: Binning based on cumulative sum with reset above threshold.conditional_rowMeans: Form row means conditional on number of non-missing.common.shared: Compute a common shared environment matrix.colCumSum: Apply cumsum to each column of matrix. ![]()
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