#STATISTICAL CALCULATIONS CALCUALTOR PLUS#

Why is sample size determination important? If used to solve for power it will output the power as a proportion and as a percentage. The sample size calculator will output the sample size of the single group or of all groups, as well as the total sample size required. The type I error rate is equivalent to the significance threshold if one is doing p-value calculations and to the confidence level if using confidence intervals. For an in-depth explanation of power see What is statistical power below. Power, calculated as 1 - ОІ, where ОІ is the type II error rate, is only required when determining sample size. The type I error rate, О±, should always be provided. See Types of null and alternative hypothesis below for an in-depth explanation.Д¦. When the superiority or non-inferiority margin is zero, it becomes a classical left or right sided hypothesis, if it is larger than zero then it becomes a true superiority / non-inferiority design. The calculator supports superiority, non-inferiority and equivalence alternative hypotheses. If entering means data, one needs to specify the mean under the null hypothesis (worst-case scenario for a composite null) and the standard deviation of the data (for a known population or estimated from a sample).ДҐ.

#STATISTICAL CALCULATIONS CALCUALTOR PLUS#

In this case the MDE (MRDE) is calculated relative to the baseline plus the superiority margin, as it is usually more intuitive to be interested in that value. For example, if the baseline mean is 10 and there is a superiority alternative hypothesis with a superiority margin of 1 and the minimum effect of interest relative to the baseline is 3, then enter an MDE of 2, since the MDE plus the superiority margin will equal exactly 3. It is always relative to the mean/proportion under H 0 В± the superiority/non-inferiority or equivalence margin. The minimum effect of interest, which is often called the minimum detectable effect ( MDE, but more accurately: MRDE, minimum reliably detectable effect) should be a difference one would not like to miss, if it existed. It is the mean one expects to observe if the treatment has no effect whatsoever.Д¤. Baseline The baseline mean (mean under H 0) is the number one would expect to see if all experiment participants were assigned to the control group. The sample size and power calculator uses the Z-distribution (normal distribution).ДЈ. One can also calculate power and sample size for the mean of just a single group. See Absolute versus relative difference for additional information. height, weight, speed, time, revenue, etc.), or the relative difference between two proportions or two means (percent difference, percent change, etc.). conversion rate or event rate), the absolute difference of two means (continuous data, e.g. The outcome of interest can be the absolute difference of two proportions (binomial data, e.g. Power calculations are not currently supported for more than one treatment group due to their complexity.Дў.

These are only approximately accurate and subject to the assumption of about equal effect size in all k groups, and can only support equal sample sizes in all groups and the control. For comparing more than one treatment group to a control group the sample size adjustments based on the Dunnett's correction are applied. The sample size calculator supports experiments in which one is gathering data on a single sample in order to compare it to a general population or known reference value (one-sample), as well as ones where a control group is compared to one or more treatment groups ( two-sample, k-sample) in order to detect differences between them. Parameters for sample size and power calculationsДЎ. Usually one would determine the sample size required given a particular power requirement, but in cases where there is a predetermined sample size one can instead calculate the power for a given effect size of interest. It can be used both as a sample size calculator and as a statistical power calculator. This calculator allows the evaluation of different statistical designs when planning an experiment (trial, test) which utilizes a Null-Hypothesis Statistical Test to make inferences.

Absolute versus relative difference and why it matters for sample size determination.

Types of null and alternative hypotheses in significance tests.

Why is sample size determination important?.

Parameters for sample size and power calculations.

Using the power & sample size calculator.

Statistical calculations calcualtor