Everything about Statistical conclusion validity
Statistical conclusion validity is the degree to which conclusions about the relationship among variables based on the data are correct or "reasonable". This began as being solely about whether the statistical conclusion about the relationship of the variables was correct, but now there is a movement towards moving to "reasonable" conclusions that use: quantitative, statistical, and qualitative data. Fundamentally, two types of errors can occur: type I and type II. Statistical conclusion validity concerns the qualities of the study that make these types of errors more likely. Statistical conclusion validity involves ensuring the use of adequate sampling procedures, appropriate statistical tests, and reliable measurement procedures. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Statistical conclusion validityA 5-minute orientation
- Skim a recent paper: The Influence of Study Selection Criteria on Statistical Conclusion Validity: A Simulation StudyInfluential work since 2022
- Pick up a classic book: Thinking, Fast and SlowThe most-reprinted book on the subject
- Read the landmark paper: Statistical Conclusion Validity: Some Common Threats and Simple RemediesCited 58 times
- Go sideways: StatisticsA closely related topic
- Go sideways: Statistical assumptionA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Statistical Conclusion Validity: Some Common Threats and Simple Remedies
Statistical Conclusion Validity of Rehabilitation Research
Statistical Conclusion Validity of Rehabilitation Research
Evaluating the statistical conclusion validity of weighted mean results in meta-analysis by analysing funnel graph diagrams
Statistical Conclusion Validity of Early Intervention Research with Handicapped Children
Statistical Conclusion Validity for Organizational Science Researchers: A Review
Confounds of insensitivity and blind luck: Statistical conclusion validity in stroke rehabilitation clinical trials
Missing Data Techniques and the Statistical Conclusion Validity of Survey-Based Alcohol and Drug Use Research Studies: A Review and Comment on Reproducibility
🆕 Influential since 2022
📚 Books worth reading
Thinking, Fast and SlowDaniel Kahneman · 2011
Technical CommunicationJohn M. Lannon · 2000
Thought and knowledgeDiane F. Halpern · 1984
EpidemiologyM. Szklo, F. Javier Nieto · 1999
Gaussian processes for machine learningCarl Edward Rasmussen · 2005
Process analytical technologyKatherine A. Bakeev · 2007
The Jackknife and BootstrapJun Shao, Dongsheng Tu · 1995
Validity and Social ExperimentationLeonard Bickman · 2000
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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