Search results for "p-value"

showing 10 items of 23 documents

Retract p < 0.005 and propose using JASP, instead

2018

Seeking to address the lack of research reproducibility in science, including psychology and the life sciences, a pragmatic solution has been raised recently:  to use a stricter p < 0.005 standard for statistical significance when claiming evidence of new discoveries. Notwithstanding its potential impact, the proposal has motivated a large mass of authors to dispute it from different philosophical and methodological angles. This article reflects on the original argument and the consequent counterarguments, and concludes with a simpler and better-suited alternative that the authors of the proposal knew about and, perhaps, should have made from their Jeffresian perspective: to use a Bayes …

0301 basic medicineData SharingOpen scienceComputer scienceresearch evidenceGeneral Biochemistry Genetics and Molecular Biology03 medical and health sciences0302 clinical medicineArgumentFrequentist inferenceOrder (exchange)practical significanceBayes factorsPrior probabilityreplicabilityp-valueGeneral Pharmacology Toxicology and Pharmaceuticsreproducibilitystatistical significancePotential impactGeneral Immunology and MicrobiologyPerspective (graphical)Bayes factorArticlesGeneral MedicineOpinion ArticleEpistemology030104 developmental biologyp-values030217 neurology & neurosurgeryF1000Research
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Rejection odds and rejection ratios: A proposal for statistical practice in testing hypotheses

2016

Much of science is (rightly or wrongly) driven by hypothesis testing. Even in situations where the hypothesis testing paradigm is correct, the common practice of basing inferences solely on p-values has been under intense criticism for over 50 years. We propose, as an alternative, the use of the odds of a correct rejection of the null hypothesis to incorrect rejection. Both pre-experimental versions (involving the power and Type I error) and post-experimental versions (depending on the actual data) are considered. Implementations are provided that range from depending only on the p-value to consideration of full Bayesian analysis. A surprise is that all implementations -- even the full Baye…

Bayes' ruleFOS: Computer and information sciencesComputer sciencemedia_common.quotation_subjectBayesian probabilityBayesian01 natural sciencesArticle050105 experimental psychologyStatistical powerOddsMethodology (stat.ME)010104 statistics & probabilityFrequentist inferenceBayes factorsEconometrics0501 psychology and cognitive sciencesp-value0101 mathematicsFrequentistPsychology(all)General PsychologyStatistics - Methodologymedia_commonMathematicsStatistical hypothesis testingApplied Mathematics05 social sciencesBayes factorSurpriseOddsNull hypothesisType I and type II errorsJournal of Mathematical Psychology
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Una procedura sequenziale di stima di punto di cambiamento

2008

In this paper we propose a sequential procedure for the estimation of a change-point when a change has occurred in the distribution that governs the process which generates the observations. The procedure applies whether the distribution functions involved are completely specified or they contain unknown parameters to be estimated. The procedure is based on the Kolmogorov-Smirnov test of goodness of fit, or an appropriate different test such as the chi-square test, and satisfies the optimality condition defined by the maximization of the sum of the p-values involved.

Change point sequential estimation p-values optimality conditionSettore SECS-S/01 - Statistica
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V: p-Werte: Was sie besagen und was nicht …

2002

Both an extensive data description and an explicit assessment of a study result's statistical significance should be presented in the result section of a clinical trial report. Whereas the description illustrates the order and clinical relevance of the study findings, the statistical significance describes its generalizability to patients not included in the clinical trial: Despite the random recruitment of patients into a trial, the study results may fail to represent clinical reality (for example the trial might show falsely positive efficacy findings, whereas in "clinical reality" efficacy appears rather limited). A p value measures the statistical significance of a study result -- the s…

Clinical trialResearch designOphthalmologyRelative riskStatistical significanceClinical significanceGeneralizability theoryp-valuePsychologyClinical psychologyStatistical hypothesis testingKlinische Monatsblätter für Augenheilkunde
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A Procedure for Selecting Representative Subsamples of a Population from a Simple Random Sample

2015

This paper proposes a procedure for selecting large subsamples drawn from a large simple random sample that are more representative of the population under study. By means of the so-called constant of proportionality, the procedure seeks to maximize the size of the subsample taken from a stratified random sample with proportional allocation, restricting it to a p-value high enough to achieve a good fit using Pearson’s chi-square goodness of fit test. The user has the freedom to choose between a larger subsample with poorer adjustment or a smaller subsample with a better fit. We use the Continuous Sample of Working Lives (CSWL), a set of micro data taken from Spanish Social Security records,…

Engineeringeducation.field_of_studybusiness.industryPopulationSample (statistics)Simple random sampleRepresentativeness heuristicStratified samplingGoodness of fitStatisticsEconometricsChi-square testp-valuebusinesseducationSSRN Electronic Journal
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Bayesian Checking of the Second Levels of Hierarchical Models

2007

Hierarchical models are increasingly used in many applications. Along with this increased use comes a desire to investigate whether the model is compatible with the observed data. Bayesian methods are well suited to eliminate the many (nuisance) parameters in these complicated models; in this paper we investigate Bayesian methods for model checking. Since we contemplate model checking as a preliminary, exploratory analysis, we concentrate on objective Bayesian methods in which careful specification of an informative prior distribution is avoided. Numerous examples are given and different proposals are investigated and critically compared.

FOS: Computer and information sciencesStatistics and ProbabilityModel checkingModel checkingComputer scienceconflictGeneral MathematicsBayesian probabilityMachine learningcomputer.software_genreMethodology (stat.ME)partial posterior predictivePrior probabilityStatistics - Methodologybusiness.industrymodel criticismProbability and statisticsExploratory analysisobjective Bayesian methodsempirical-Bayesposterior predictivep-valuesArtificial intelligenceStatistics Probability and Uncertaintybusinesscomputer
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Falacias sobre el valor p compartidas por profesores y estudiantes universitarios

2017

Resumen La “Práctica Basada en la Evidencia” exige que los profesionales valoren de forma crítica los resultados de las investigaciones psicológicas. Sin embargo, las interpretaciones incorrectas de los valores p de probabilidad son abundantes y repetitivas. Estas interpretaciones incorrectas afectan a las decisiones profesionales y ponen en riesgo la calidad de las intervenciones y la acumulación de un conocimiento científico válido. Identificar el tipo de falacia que subyace a las decisiones estadísticas es fundamental para abordar y planificar estrategias de educación estadística dirigidas a intervenir sobre las interpretaciones incorrectas. En consecuencia, el objetivo de este estudio e…

FallacyEvidence-based practicePsychological researchInterpretation (philosophy)05 social sciencesPsychological intervention050109 social psychologyComprehensionStatistical significance0501 psychology and cognitive sciencesp-valuePsychologySocial psychologyGeneral Psychology050104 developmental & child psychologyUniversitas Psychologica
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Misconceptions of the p-value among Chilean and Italian academic psychologists

2016

Common misconceptions of p-values are based on certain beliefs and attributions about the significance of the results. Thus, they affect the professionals' decisions and jeopardize the quality of interventions and the accumulation of valid scientific knowledge. We conducted a survey on 164 academic psychologists (134 Italian, 30 Chilean) questioned on this topic. Our findings are consistent with previous research and suggest that some participants do not know how to correctly interpret p-values. The inverse probability fallacy presents the greatest comprehension problems, followed by the replication fallacy. These results highlight the importance of the statistical re-education of researche…

Fallacyp-value misconceptionsSociology of scientific knowledgePsychology (all)Education; High education; p-value misconceptions; Statistical cognition; Survey; Psychology (all)05 social sciencesPsychological intervention050109 social psychologyCognitionAffect (psychology)050105 experimental psychologyEducationComprehensionPsychology0501 psychology and cognitive sciencesStatistical cognitionAttributionPsychologySurveySocial psychologyKnow-howGeneral PsychologyOriginal ResearchHigh education
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Confidence Interval or P-Value?: Part 4 of a Series on Evaluation of Scientific Publications

2009

An understanding of p-values and confidence intervals is necessary for the evaluation of scientific articles. This article will inform the reader of the meaning and interpretation of these two statistical concepts.The uses of these two statistical concepts and the differences between them are discussed on the basis of a selective literature search concerning the methods employed in scientific articles.P-values in scientific studies are used to determine whether a null hypothesis formulated before the performance of the study is to be accepted or rejected. In exploratory studies, p-values enable the recognition of any statistically noteworthy findings. Confidence intervals provide informatio…

Frequentist probabilitySeries (mathematics)business.industryInterpretation (philosophy)ScienceReproducibility of ResultsGeneral MedicineReview ArticleMeasure (mathematics)Sensitivity and SpecificityConfidence intervalData Interpretation StatisticalStatisticsConfidence IntervalsMedicinep-valuePeriodicals as TopicbusinessAlgorithms
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Improving the Representativeness of a Simple Random Sample: An Optimization Model and Its Application to the Continuous Sample of Working Lives

2020

This paper proposes an optimization model for selecting a larger subsample that improves the representativeness of a simple random sample previously obtained from a population larger than the population of interest. The problem formulation involves convex mixed-integer nonlinear programming (convex MINLP) and is, therefore, NP-hard. However, the solution is found by maximizing the size of the subsample taken from a stratified random sample with proportional allocation and restricting it to a p-value large enough to achieve a good fit to the population of interest using Pearson&rsquo

General MathematicsPopulation0211 other engineering and technologiessubsamplingSample (statistics)02 engineering and technologyRepresentativeness heuristic:CIENCIAS ECONÓMICAS [UNESCO]Nonlinear programming0502 economics and businessStatisticsComputer Science (miscellaneous)Chi-square testchi-square testp-value050207 economicseducationEngineering (miscellaneous)Mathematicseducation.field_of_study021103 operations researchlcsh:Mathematics05 social sciencesUNESCO::CIENCIAS ECONÓMICASp-valueSimple random samplelcsh:QA1-939Stratified samplingOptimización matemáticacontinuous sample of working livesEconomía públicaoptimizationMathematics
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