Literature DB >> 30034025

Hypothesis Testing in the Real World.

Jeff Miller1.   

Abstract

Critics of null hypothesis significance testing suggest that (a) its basic logic is invalid and (b) it addresses a question that is of no interest. In contrast to (a), I argue that the underlying logic of hypothesis testing is actually extremely straightforward and compelling. To substantiate that, I present examples showing that hypothesis testing logic is routinely used in everyday life. These same examples also refute (b) by showing circumstances in which the logic of hypothesis testing addresses a question of prime interest. Null hypothesis significance testing may sometimes be misunderstood or misapplied, but these problems should be addressed by improved education.

Keywords:  common sense logic; hypothesis testing; statistical methods

Year:  2016        PMID: 30034025      PMCID: PMC5991789          DOI: 10.1177/0013164416667984

Source DB:  PubMed          Journal:  Educ Psychol Meas        ISSN: 0013-1644            Impact factor:   2.821


  18 in total

1.  Tests of significance considered as evidence. Journal of the American Statistical Association 1942;37:325-35.

Authors:  Joseph Berkson
Journal:  Int J Epidemiol       Date:  2003-10       Impact factor: 7.196

2.  Testing the null hypothesis and the strategy and tactics of investigating theoretical models.

Authors:  D A GRANT
Journal:  Psychol Rev       Date:  1962-01       Impact factor: 8.934

3.  False-positive psychology: undisclosed flexibility in data collection and analysis allows presenting anything as significant.

Authors:  Joseph P Simmons; Leif D Nelson; Uri Simonsohn
Journal:  Psychol Sci       Date:  2011-10-17

4.  A practical solution to the pervasive problems of p values.

Authors:  Eric-Jan Wagenmakers
Journal:  Psychon Bull Rev       Date:  2007-10

5.  How to quantify support for and against the null hypothesis: a flexible WinBUGS implementation of a default Bayesian t test.

Authors:  Ruud Wetzels; Jeroen G W Raaijmakers; Emöke Jakab; Eric-Jan Wagenmakers
Journal:  Psychon Bull Rev       Date:  2009-08

6.  Statistics: P values are just the tip of the iceberg.

Authors:  Jeffrey T Leek; Roger D Peng
Journal:  Nature       Date:  2015-04-30       Impact factor: 49.962

7.  The Rules of the Game Called Psychological Science.

Authors:  Marjan Bakker; Annette van Dijk; Jelte M Wicherts
Journal:  Perspect Psychol Sci       Date:  2012-11

8.  P values and statistical practice.

Authors:  Andrew Gelman
Journal:  Epidemiology       Date:  2013-01       Impact factor: 4.822

Review 9.  Publication bias and the failure of replication in experimental psychology.

Authors:  Gregory Francis
Journal:  Psychon Bull Rev       Date:  2012-12

10.  Why most published research findings are false.

Authors:  John P A Ioannidis
Journal:  PLoS Med       Date:  2005-08-30       Impact factor: 11.613

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  1 in total

1.  The Practical Alternative to the p Value Is the Correctly Used p Value.

Authors:  Daniël Lakens
Journal:  Perspect Psychol Sci       Date:  2021-02-09
  1 in total

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