**520 power-analysis questions.**

I am running a longitudinal experiment on 75 plants. For logistical reasons, there is no control group -- all plants receive the treatment.
To assess the outcome of the experiment, I need to run a ...

My understanding of statistical power is that it is the likelihood of correctly rejecting the null hypothesis, with low power meaning you are very likely to make a beta error (failing to reject the ...

I have installed the R package "pwr" and I am looking to use it for my experiment to see how much power the tests will have.
The experiment is a $3^3$ factorial design ($3$ factors, each with $3$ ...

I am performing a conditional logistics regression (CLR) case-control (1:3) study over a very large dataset that has been partitioned according to a set of study requirements (to follow). Each entry ...

We have a density $X$ defined as $f(x,\theta)=\theta x^{\theta -1}I_{(0,1)}(x)$.
The hypothesis to test is given as follows:
$H_0:\theta \leq1$ Vs $H_1:\theta >1$
A sample size of two is selected,...

I have a null result for a negative binomial regression model and I would like to give evidence that my sample is large enough to detect even small effects.
I've found a few online calculators for ...

I have a dataset with a response variable and a predictor variable. I want to calculate the possible difference of AUC (delta) I can find with power = 0.8 and significance level = 0.05. Let's say I ...

Imagine a researcher conducted an experiment and tested an hypothesis using a two independent samples approach. It was the first experiment of this kind, so the researcher had no idea about a possible ...

I'm designing an epidemiological retrospective cohort study with a large number of exposures and outcomes, and I'm trying to figure out how many subjects I'll need in order to run all my analyses. The ...

I need suggestions for how to calculate the $n$ required for 80% and 90% power for >30% change from baseline ($T_0$) at $T_1$ or $T_2$, drug vs. placebo, 2:1 ratio; 20% CV in test; factors: subject, ...

I have found no answer on web search engines for that. And even though I was able to find here some answers on how to calculate the power of a Welch's t-test here, they were expressed in R code.
As I ...

I keep reading "effect size is independent of sample size" on the interwebs. Don't get me wrong, I get the practical vs statistical significance considerations.
What I don't get is that;
-power,...

I am trying to estimate the sample size needed to have an effect size of 2.4, with power=0.8 and alpha=0.05. The outcome variable has 8 levels and each individual has 8 observations. The model has ...

I would like to estimate the power of an average treatment effect, across a cohort split into subjects nested in sites. I provide a complete code example below that generates fake data given hyper-...

I am running a study on school children to compare psychometrics in physically active and sedentary children.
My IV is physical activity with 2 levels - physically active / sedentary
and DV ...

Suppose, I am generating data from bivariate normal distribution with means 0 and variances 1 and correlation coefficient 0,0.5 and 1. I need to calculate power for different correlations.
I am doing ...

I read everywhere that repeated measures ANOVA is inferior to mixed modelling (since it doesn't handle missing data as well and relies on sphericity assumption). G*Power doesn't tell you how to ...

There are helpful questions and answers for how to calculate the required sample size (or carry out a power analysis) for MANOVA, but not for MANCOVA using the freely-available G Power software.
Is ...

I'm running a economic experiment. From a previous pilot I already know which size of treatment-effect I can expect. Each participant plays 20 rounds, so it't a repeated measures approach. I want to ...

I'm using G*Power to work out how many participants I need. I'll be using a MANOVA, I have two independent variables (Male and Female) and they will be answering 13 different questionnaires so 13 ...

I have a question about an a priori statistical power analysis. I am used to using between-subjects experimental designs, in which I usually need about 180 participants, using a small to medium size ...

Running into a little bit of an issue with an experiment.
Basically, I'd like to make a change in a process that may or may not reduce the variation in production. The mean value of the process is ...

I have looked everywhere and have not found an answer to my specific design question related to computing the sample size necessary for (specifically) a 2 X 2 X 2 ANOVA.
Specifically, using G*Power ...

I'm trying to understand what's happening in the article Using simulation to estimate the power of a statistical test
I'm familiar with bootstrapping which makes sense to me. But I don't understand ...

I would welcome any help with computing power calculations for cluster randomised control trial and specifying the code in R for this. I've been trying to use clusterPower package but any R package ...

I am writing a grant application which will be evaluating a new diagnostic test. The test will predict whether a patient with lung fibrosis will remain stable or progress. I am using an existing ...

I'm attempting to calculate n for a trial in medical imaging comparing two different imaging modalities. I've never done this before, so I'm not sure how to approach this and interpret the result.
...

I am planning a research experiment with a 4x2 within-subjects design, and am currently trying to determine an appropriate sample size for my project (in order to achieve desired power with an effect ...

"Because (this study) collected 77 participants in total, and used an alpha level of .05, the critical t-value is 1.99. This critical t-value can be transformed into a 'critical standardized effect ...

Say I have two devices that purifies milk, device A and device B. I assume Device B is better and it produces milk that is 5% better than A. If I want to test this assumption, I take 8 sample from the ...

I need to estimate the required sample size for a future study with a nested design and thus, mixed effect regression.
Sampling will take place at six plots per study site and observations will thus,...

I conducted an unfunded study where 3 groups of 15 participants were observed over 11 timepoints. There were statistically significant between-group differences in slope and also statistically ...

Imagine I have a sample distribution for a circular data set with a mean group direction and known variation. I would like to do a power analysis for a known effect size (e.g. to determine what sample ...

I am designing an experiment and want to define the sample size. To identify this, I am setting my significance level to 0.05 and the power to 0.8. My alternative hypotheses says the two means should ...

I know power is the likelihood of correctly rejecting the null hypothesis, but I just want to check that my interpretation of it with the detectable difference is correct.
Consider a 2 sample test ...

I would like to perform a power analysis on Gpower. The only bit of information that I have is provided in the image below:
This is what I have done so far:
Am I doing it right ?
Thank you

I have a study where I need to estimate the needed sample size to reliably determine the SD. In this case the means are irrelevant, as only the SD carry meaning. I have tried to find a solution for ...

I have been taught that under-powered trials cause effects of practical importance being not detected. Thus, that's the reason why we mainly work with power >= 0.8. However, I'm curious..
In what ...

I have a problem of sample size for my research paper approval. I could only ran the statistics on 5 subjects for both plantar pressure and temperature measurements but the statistical power seems to ...

I have a chunk of text and I cannot work out what the authors are trying to say with within-between factors. Why does the power requirement go from 58 to 18?
Statistical power analysis was ...

I need to perform a (two-sample) power analysis, however my data are differently distributed in both samples and I am not sure whether I can a standard approach through t-test.
Please see the ...

I would like to calculate the power of a Chi-Square test for goodness-of-fit as a function of sample size for a specified alpha-value (say 0.01). Specifically, I am referring to power as the ...

I need to run a power analysis in order to discover a sample size for an experiment. The majority of experiments our lab runs are repeated measures studies that use no between subjects variables but ...

I used R package pwr (G*Power gives the same result) which say for a one-sided t-test of means with alpha=.05, beta=.20, that I would need 40 samples for both control and treatment groups (n=80) to ...

Is it correct (perhaps at least as a good approximation) to determine sample size via a power analysis that assumes an infinite population and then to adjust the required sample size by a finite ...

I am doing a one-way ANOVA of a response variable (Y) on a treatment factor (T) of 7 levels. However, for each treatment, I have only 2 observations (or replicates). The ANOVA result shows the the ...

I am investigating the effects of learning on cultural distinctive school childrenâ€™s academic performance from a root cause of Social Mediation which has three categories: cultural language, ...

Imagine I have a population of a known size (e.g., 100,000 voters), and I know they can only vote for A, B, C, D or E.
If a random sample of 100 voters are, e.g., A = 40%, B = 30%, C = 10%, D = 10%, ...

I am running a MaxDiff experiment where there will be four different "arms". Essentially, a respondent will be assigned to one of four conditions, where they will be shown one of three messages (plus ...

As a part of my master thesis, I'm conducting an observational study of journalists' background and the effect of this on the approach to a certain case study. I have a fixed number of observations/...

- sample-size
- power
- hypothesis-testing
- r
- anova
- statistical-significance
- logistic
- t-test
- effect-size
- repeated-measures
- simulation
- experiment-design
- regression
- mixed-model
- gpower
- correlation
- binomial
- clinical-trials
- multiple-regression
- chi-squared
- multiple-comparisons
- sampling
- proportion
- post-hoc
- confidence-interval

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