#statstab #360 Bayes Factor Design Analysis {bfda}
Thoughts: Sample size planning is confusing at first with Bayesian. But BFDA is the quick answer.
#statstab #360 Bayes Factor Design Analysis {bfda}
Thoughts: Sample size planning is confusing at first with Bayesian. But BFDA is the quick answer.
π¨New blog post π: Your Study Is Too Small (If You Care About Practically Significant Effects)
#effectsize #precision #poweranalysis #research #Psychology #MCID #SESOI #samplesize
How large should your sample size be?
https://vickiboykis.com/2015/08/04/how-large-should-your-sample-size-be/
#HackerNews #sampleSize #statistics #research #dataScience #methodology
#statstab #353 The Abuse of Power; The Pervasive Fallacy of Power Calculations for Data Analysis
Thoughts: An seminal paper on "post hoc" power calculations.
#power #QRPs #NHST #posthoc #samplesize #effectsize
https://www.tandfonline.com/doi/abs/10.1198/000313001300339897
#statstab #324 Information loss due to dichotomization of the outcome of clinical trials. Also it costs more! π°
Thoughts: Killing the variance in your outcome measure is *not* data transformation.
#statstab #312 {presize} pkg: Understanding Precision-Based Sample Size Calculations
Thoughts: Do you care about effect sizes? Then precision-based planning is for you. Expect higher Ns!
#r #samplesize #precision #estimation #power #Confidenceintervals
https://library.virginia.edu/data/articles/understanding-precision-based-sample-size-calculations
#statstab #297 Sample sizes for saturation in qualitative research
Thoughts: A complicated (and contentious) topic for quals research.
#qualitative #research #sample #samplesize #saturation #methodology #guide #review
https://www.sciencedirect.com/science/article/pii/S0277953621008558
Application of JNDs to meta-science. Very sensible!
"For example, in clinical settings researchers may specify this smallest effect size of interest as the smallest difference in a health condition that patients themselves notice...this practice has been used at least since the advent of psychophysics in the second half of the 19th century"
#metascience #psychology #neuroscience #effectsize #psychophysics #samplesize
`This review holds two main aims. The first aim is to explain the importance of sample size and its relationship to effect size (ES) and statistical significance. The second aim is to assist researchers planning to perform sample size estimations by suggesting and elucidating available alternative software, guidelines and references that will serve different scientific purposes.`
I'll be offering an introduction to #simulation methods to determine #SampleSize-s for clustered / nested studies.
Apparently another popular session at #RMeF23 π
One of the classics that got me into this area is Ukoumunne's
https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.1330
I was always interested in how to straddle the overlap between observational #TherapistEffect studies* and #RCTs in this area.
* eg., https://rdcu.be/dqi20
R to @Plants_EFSA: Second and last day: participants are working in groups to complete the exercise on surveillance optimisation by stats tool
#SampleSize
#ConfidenceLevel
#MethodSensitivity
#PestTrapping
#VisualInspection
#PlantHealth
π¦π: https://nitter.cz/Plants_EFSA/status/1717545957733142715#m
[2023-10-26 14:17 UTC]
One of the most problematic areas in the submission we get and papers I review are the sections on #SampleSize justifications.
See for example @lakens' excellent paper on the topic:
https://psyarxiv.com/9d3yf/
It now comes with a process guide in a #ShinyApp, which is an excellent support:
https://shiny.ieis.tue.nl/sample_size_justification/
#Rstats
For #HRQL researchers:
https://rdcu.be/dnfO4
And many people teach this stuff, e.g., βΊοΈ
https://www.researchgate.net/publication/335813329_Estimating_sample_sizes_based_on_required_precision_for_surveys_and_epidemiological_research
#StudyDesign #NightshiftEditor
[edit: typo in hashtag]
My student at is running a personalty study and needs a huge number of participants! Please consider taking 5-10mins to complete this survey! https://mmu.eu.qualtrics.com/jfe/form/SV_eJ5lqgociAiTWB0 #psychology #personality #samplesize #data
Online #workshop:
Simulation-based power analyses in (generalized) linear mixed models
17.05.2023, 10-12h CEST
The workshop will cover basics of power analysis, linear mixed models, and why the combination of both requires a simulation-based approach.
In my experience, this is for many areas of #HealthSciences and #HRQL research a key problem when designing studies.
Maybe worth a read as well:
https://link.springer.com/article/10.3758/s13428-021-01546-0
My latest post - OC Curve and Reliability/Confidence Sample Sizes:
#SampleSize #Statistics #Reliability #Confidence #Minitab
I have had a lot of feedback on one of my earlier posts on OC curves and how one can use it to generate a reliability/confidence statement based on sample size, n and rejects, c. This post is mostly geared towards giving an overview of using OC curves to generate reliability/confidence values and using Minitab to do the same.
https://harishsnotebook.wordpress.com/2023/03/25/oc-curve-and-reliability-confidence-sample-sizes/
Can anyone point me to a paper/post explaining why you should not base your sample size calculation on the effect found in the literature or a pre-test? Pretty sure I read it once but cannot find it anymore. Maybe I saw it in @lakens's course? #poweranalysis #samplesize
Find all the reviews from our Microbial IMPACTT review series with Mucosal Immunology in one convenient place: https://www.mucosalimmunology.org/microbial-impactt
#review #immunology #microbiome #mucosalimmunology #germfree #IBD #wildmicrobiome #microbiota #metabolomics #power #samplesize #metabolites
Iβm a #SampleSize of precisely one, but Iβve been taking #Flonase for a year to deal with seasonal allergies and I havenβt had so much as a runny nose in that time.
This looks fascinating:
βWe reviewed empirically-based studies of sample sizes for saturation in qualitative research.
We confirmed qualitative studies can reach saturation at relatively small sample sizes.
Results show 9β17 interviews or 4β8 focus group discussions reached saturation.β
#qualitative #research #saturation #samplesize #academicchatter
https://www.sciencedirect.com/science/article/pii/S0277953621008558
(Interested in) Working with the random-intercept Cross-lagged Panel Model and unsure what sample size to use?
Jeroen Mulder fixed it for you:
Mulder, J.D., (2022). Power analysis for the random intercept cross-lagged panel model using the powRICLPM R-package. Structural Equation Modeling: A Multidisciplinary Journal.
https://jeroendmulder.github.io/powRICLPM/
Other questions about the RI-CLPM?
https://jeroendmulder.github.io/RI-CLPM/index.html
#SEM #longitudinal #PanelData #RICLPM #CLPM #Dynamics #power #SampleSize