Moc testu (Polish Wikipedia)

Analysis of information sources in references of the Wikipedia article "Moc testu" in Polish language version.

refsWebsite

Global rank Polish rank

26doi.org

2^nd place

6^th place

21worldcat.org

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2^nd place

9nih.gov

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3apa.org

1,220^th place

1,025^th place

2nature.com

234^th place

204^th place

2elsevier.com

610^th place

682^nd place

1archive.org

6^th place

33^rd place

1columbia.edu

488^th place

1,229^th place

1psychbrief.com

low place

1osf.io

7,153^rd place

low place

1jamanetwork.com

2,650^th place

1,846^th place

1wayne.edu

8,028^th place

low place

1sciencedirect.com

149^th place

235^th place

apa.org

psycnet.apa.org

JacobJ. Cohen JacobJ., A power primer., „Psychological Bulletin”, 112 (1), 1992, s. 155–159, DOI: 10.1037/0033-2909.112.1.155, ISSN 1939-1455 [dostęp 2017-01-31] (ang.).
F.D.F.D. Richard F.D.F.D., Charles F.Ch.F. Bond Charles F.Ch.F., Juli J.J.J. Stokes-Zoota Juli J.J.J., One Hundred Years of Social Psychology Quantitatively Described., „Review of General Psychology”, 4, 2003, s. 331–363, DOI: 10.1037/1089-2680.7.4.331, ISSN 1939-1552 [dostęp 2017-01-06] .
Statistical methods in psychology journals: Guidelines and explanations., „American Psychologist”, 8, 1999, DOI: 10.1037/0003-066X.54.8.594, ISSN 1935-990X [dostęp 2017-01-06] .

archive.org

DavidD. Colquhoun DavidD., Lectures on Biostatistics An Introduction to Statistics with Applications in Biology and Medicine, Oxford University Press, 1971, s. 96-97 [dostęp 2017-01-09] .

columbia.edu

statmodeling.stat.columbia.edu

AndrewA. Gelman AndrewA., You need 16 times the sample size to estimate an interaction than to estimate a main effect « Statistical Modeling, Causal Inference, and Social Science [online], statmodeling.stat.columbia.edu [dostęp 2019-03-31] .

doi.org

dx.doi.org

JacobJ. Cohen JacobJ., A power primer., „Psychological Bulletin”, 112 (1), 1992, s. 155–159, DOI: 10.1037/0033-2909.112.1.155, ISSN 1939-1455 [dostęp 2017-01-31] (ang.).
Marcus R.M.R. Munafò Marcus R.M.R. i inni, Power failure: why small sample size undermines the reliability of neuroscience, „Nature Reviews Neuroscience”, 14 (5), 2013, s. 365–376, DOI: 10.1038/nrn3475, ISSN 1471-0048 [dostęp 2019-03-31] (ang.).
AndrewA. Gelman AndrewA., JohnJ. Carlin JohnJ., Beyond Power Calculations: Assessing Type S (Sign) and Type M (Magnitude) Errors, „Perspectives on Psychological Science”, 9 (6), 2014, s. 641–651, DOI: 10.1177/1745691614551642, ISSN 1745-6916 [dostęp 2019-03-31] (ang.).
Eric-JanE.J. Wagenmakers Eric-JanE.J. i inni, A power fallacy, „Behavior Research Methods”, 47 (4), 2015, s. 913–917, DOI: 10.3758/s13428-014-0517-4, ISSN 1554-3528 [dostęp 2019-03-31] (ang.).
Felix D.F.D. Schönbrodt Felix D.F.D., MarcoM. Perugini MarcoM., At what sample size do correlations stabilize?, „Journal of Research in Personality”, 47 (5), 2013, s. 609–612, DOI: 10.1016/j.jrp.2013.05.009 [dostęp 2019-03-31] (ang.).
DaniëlD. Lakens DaniëlD., Equivalence Tests: A Practical Primer for t Tests, Correlations, and Meta-Analyses, „Social Psychological and Personality Science”, 8 (4), 2017, s. 355–362, DOI: 10.1177/1948550617697177, ISSN 1948-5506, PMID: 28736600, PMCID: PMC5502906 [dostęp 2019-03-31] (ang.).
FaridF. Anvari FaridF., DanielD. Lakens DanielD., Using Anchor-Based Methods to Determine the Smallest Effect Size of Interest, DOI: 10.31234/osf.io/syp5a [dostęp 2019-03-31] .
CasperC. Albers CasperC., DaniëlD. Lakens DaniëlD., When power analyses based on pilot data are biased: Inaccurate effect size estimators and follow-up bias, „Journal of Experimental Social Psychology”, 74, 2018, s. 187–195, DOI: 10.1016/j.jesp.2017.09.004 [dostęp 2019-03-31] (ang.).
John MJ.M. Hoenig John MJ.M., Dennis MD.M. Heisey Dennis MD.M., The Abuse of Power: The Pervasive Fallacy of Power Calculations for Data Analysis, „The American Statistician”, 55 (1), 2001, s. 19–24, DOI: 10.1198/000313001300339897, ISSN 0003-1305 [dostęp 2019-03-31] (ang.).
JeehyoungJ. Kim JeehyoungJ., Bong SooB.S. Seo Bong SooB.S., How to Calculate Sample Size and Why, „Clinics in Orthopedic Surgery”, 5 (3), 2017, s. 235–242, DOI: 10.4055/cios.2013.5.3.235, ISSN 2005-291X, PMID: 24009911, PMCID: PMC3758995 [dostęp 2017-01-31] .
Helena ChmuraH.Ch. Kraemer Helena ChmuraH.Ch. i inni, Caution Regarding the Use of Pilot Studies to Guide Power Calculations for Study Proposals, „Archives of General Psychiatry”, 63 (5), 2006, DOI: 10.1001/archpsyc.63.5.484, ISSN 0003-990X [dostęp 2017-01-31] (ang.).
DaniëlD. Lakens DaniëlD., Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs, „Frontiers in Psychology”, 4, 2013, DOI: 10.3389/fpsyg.2013.00863, ISSN 1664-1078, PMID: 24324449, PMCID: PMC3840331 [dostęp 2017-01-31] .
David M.D.M. Erceg-Hurn David M.D.M., Vikki M.V.M. Mirosevich Vikki M.V.M., Modern robust statistical methods: an easy way to maximize the accuracy and power of your research, „The American Psychologist”, 63 (7), 2008, s. 591–601, DOI: 10.1037/0003-066X.63.7.591, ISSN 0003-066X, PMID: 18855490 [dostęp 2017-02-01] .
Jeffrey N.J.N. Rouder Jeffrey N.J.N., Julia M.J.M. Haaf Julia M.J.M., Power, Dominance, and Constraint: A Note on the Appeal of Different Design Traditions, „Advances in Methods and Practices in Psychological Science”, 1 (1), 2018, s. 19–26, DOI: 10.1177/2515245917745058, ISSN 2515-2459 [dostęp 2019-03-31] (ang.).
FranzF. Faul FranzF. i inni, Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses, „Behavior Research Methods”, 41 (4), 2009, s. 1149–1160, DOI: 10.3758/BRM.41.4.1149, ISSN 1554-3528 [dostęp 2019-03-31] (ang.).
Katherine S.K.S. Button Katherine S.K.S. i inni, Power failure: why small sample size undermines the reliability of neuroscience, „Nature Reviews Neuroscience”, 5, 2013, s. 365–376, DOI: 10.1038/nrn3475, ISSN 1471-003X [dostęp 2017-01-06] (ang.).
Frank A.F.A. Bosco Frank A.F.A. i inni, Correlational effect size benchmarks, „The Journal of Applied Psychology”, 2, 2015, s. 431–449, DOI: 10.1037/a0038047, ISSN 1939-1854, PMID: 25314367 [dostęp 2017-01-06] .
F.D.F.D. Richard F.D.F.D., Charles F.Ch.F. Bond Charles F.Ch.F., Juli J.J.J. Stokes-Zoota Juli J.J.J., One Hundred Years of Social Psychology Quantitatively Described., „Review of General Psychology”, 4, 2003, s. 331–363, DOI: 10.1037/1089-2680.7.4.331, ISSN 1939-1552 [dostęp 2017-01-06] .
ToreT. Dybå ToreT., Vigdis ByV.B. Kampenes Vigdis ByV.B., Dag I.K.D.I.K. Sjøberg Dag I.K.D.I.K., A systematic review of statistical power in software engineering experiments, „Information and Software Technology”, 8, 2006, s. 745–755, DOI: 10.1016/j.infsof.2005.08.009 [dostęp 2017-01-06] .
T.D.T.D. Stanley T.D.T.D., Evan C.E.C. Carter Evan C.E.C., HristosH. Doucouliagos HristosH., What meta-analyses reveal about the replicability of psychological research., „Psychological Bulletin”, 144 (12), 2018, s. 1325–1346, DOI: 10.1037/bul0000169, ISSN 1939-1455 [dostęp 2019-03-31] (ang.).
John P.A.J.P.A. Ioannidis John P.A.J.P.A., Why most discovered true associations are inflated, „Epidemiology (Cambridge, Mass.)”, 5, 2008, s. 640–648, DOI: 10.1097/EDE.0b013e31818131e7, ISSN 1531-5487, PMID: 18633328 [dostęp 2017-01-06] .
John P.A.J.P.A. Ioannidis John P.A.J.P.A., Why Most Published Research Findings Are False, „PLOS Medicine”, 8, 2005, e124, DOI: 10.1371/journal.pmed.0020124, ISSN 1549-1676, PMID: 16060722, PMCID: PMC1182327 [dostęp 2017-01-06] .
Statistical methods in psychology journals: Guidelines and explanations., „American Psychologist”, 8, 1999, DOI: 10.1037/0003-066X.54.8.594, ISSN 1935-990X [dostęp 2017-01-06] .
D.D. Lakens D.D., E.R.K.E.R.K. Evers E.R.K.E.R.K., Sailing From the Seas of Chaos Into the Corridor of Stability: Practical Recommendations to Increase the Informational Value of Studies, „Perspectives on Psychological Science”, 3, 2014, s. 278–292, DOI: 10.1177/1745691614528520 [dostęp 2017-01-06] (ang.).
Open ScienceO.S. Collaboration Open ScienceO.S., An Open, Large-Scale, Collaborative Effort to Estimate the Reproducibility of Psychological Science, „Perspectives on Psychological Science”, 6, 2012, s. 657–660, DOI: 10.1177/1745691612462588 [dostęp 2017-01-06] (ang.).
DanielD. Lakens DanielD., Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs, „Cognition”, 4, 2013, s. 863, DOI: 10.3389/fpsyg.2013.00863, PMID: 24324449, PMCID: PMC3840331 [dostęp 2017-01-06] .

elsevier.com

linkinghub.elsevier.com

Felix D.F.D. Schönbrodt Felix D.F.D., MarcoM. Perugini MarcoM., At what sample size do correlations stabilize?, „Journal of Research in Personality”, 47 (5), 2013, s. 609–612, DOI: 10.1016/j.jrp.2013.05.009 [dostęp 2019-03-31] (ang.).
CasperC. Albers CasperC., DaniëlD. Lakens DaniëlD., When power analyses based on pilot data are biased: Inaccurate effect size estimators and follow-up bias, „Journal of Experimental Social Psychology”, 74, 2018, s. 187–195, DOI: 10.1016/j.jesp.2017.09.004 [dostęp 2019-03-31] (ang.).

jamanetwork.com

Helena ChmuraH.Ch. Kraemer Helena ChmuraH.Ch. i inni, Caution Regarding the Use of Pilot Studies to Guide Power Calculations for Study Proposals, „Archives of General Psychiatry”, 63 (5), 2006, DOI: 10.1001/archpsyc.63.5.484, ISSN 0003-990X [dostęp 2017-01-31] (ang.).

nature.com

Marcus R.M.R. Munafò Marcus R.M.R. i inni, Power failure: why small sample size undermines the reliability of neuroscience, „Nature Reviews Neuroscience”, 14 (5), 2013, s. 365–376, DOI: 10.1038/nrn3475, ISSN 1471-0048 [dostęp 2019-03-31] (ang.).
Katherine S.K.S. Button Katherine S.K.S. i inni, Power failure: why small sample size undermines the reliability of neuroscience, „Nature Reviews Neuroscience”, 5, 2013, s. 365–376, DOI: 10.1038/nrn3475, ISSN 1471-003X [dostęp 2017-01-06] (ang.).

nih.gov

ncbi.nlm.nih.gov

DaniëlD. Lakens DaniëlD., Equivalence Tests: A Practical Primer for t Tests, Correlations, and Meta-Analyses, „Social Psychological and Personality Science”, 8 (4), 2017, s. 355–362, DOI: 10.1177/1948550617697177, ISSN 1948-5506, PMID: 28736600, PMCID: PMC5502906 [dostęp 2019-03-31] (ang.).
JeehyoungJ. Kim JeehyoungJ., Bong SooB.S. Seo Bong SooB.S., How to Calculate Sample Size and Why, „Clinics in Orthopedic Surgery”, 5 (3), 2017, s. 235–242, DOI: 10.4055/cios.2013.5.3.235, ISSN 2005-291X, PMID: 24009911, PMCID: PMC3758995 [dostęp 2017-01-31] .
DaniëlD. Lakens DaniëlD., Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs, „Frontiers in Psychology”, 4, 2013, DOI: 10.3389/fpsyg.2013.00863, ISSN 1664-1078, PMID: 24324449, PMCID: PMC3840331 [dostęp 2017-01-31] .
David M.D.M. Erceg-Hurn David M.D.M., Vikki M.V.M. Mirosevich Vikki M.V.M., Modern robust statistical methods: an easy way to maximize the accuracy and power of your research, „The American Psychologist”, 63 (7), 2008, s. 591–601, DOI: 10.1037/0003-066X.63.7.591, ISSN 0003-066X, PMID: 18855490 [dostęp 2017-02-01] .
J.S.J.S. Rossi J.S.J.S., Statistical power of psychological research: what have we gained in 20 years?, „Journal of Consulting and Clinical Psychology”, 5, 1990, s. 646–656, ISSN 0022-006X, PMID: 2254513 [dostęp 2017-01-06] .
Frank A.F.A. Bosco Frank A.F.A. i inni, Correlational effect size benchmarks, „The Journal of Applied Psychology”, 2, 2015, s. 431–449, DOI: 10.1037/a0038047, ISSN 1939-1854, PMID: 25314367 [dostęp 2017-01-06] .
John P.A.J.P.A. Ioannidis John P.A.J.P.A., Why most discovered true associations are inflated, „Epidemiology (Cambridge, Mass.)”, 5, 2008, s. 640–648, DOI: 10.1097/EDE.0b013e31818131e7, ISSN 1531-5487, PMID: 18633328 [dostęp 2017-01-06] .
John P.A.J.P.A. Ioannidis John P.A.J.P.A., Why Most Published Research Findings Are False, „PLOS Medicine”, 8, 2005, e124, DOI: 10.1371/journal.pmed.0020124, ISSN 1549-1676, PMID: 16060722, PMCID: PMC1182327 [dostęp 2017-01-06] .
DanielD. Lakens DanielD., Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs, „Cognition”, 4, 2013, s. 863, DOI: 10.3389/fpsyg.2013.00863, PMID: 24324449, PMCID: PMC3840331 [dostęp 2017-01-06] .

osf.io

FaridF. Anvari FaridF., DanielD. Lakens DanielD., Using Anchor-Based Methods to Determine the Smallest Effect Size of Interest, DOI: 10.31234/osf.io/syp5a [dostęp 2019-03-31] .

psychbrief.com

Why you should think of statistical power as a curve [online], PsychBrief, 14 grudnia 2017 [dostęp 2019-03-31] (ang.).

sciencedirect.com

ToreT. Dybå ToreT., Vigdis ByV.B. Kampenes Vigdis ByV.B., Dag I.K.D.I.K. Sjøberg Dag I.K.D.I.K., A systematic review of statistical power in software engineering experiments, „Information and Software Technology”, 8, 2006, s. 745–755, DOI: 10.1016/j.infsof.2005.08.009 [dostęp 2017-01-06] .

wayne.edu

digitalcommons.wayne.edu

Kanyongo i inni, Reliability and Statistical Power: How Measurement Fallibility Affects Power and Required Sample Sizes for Several Parametric and Nonparametric Statistics, „Journal of Modern Applied Statistical Methods”, 6 (1), 2007 [dostęp 2017-01-31] (ang.).

worldcat.org

Cohen, Jacob, 1923-1998., Statistical power analysis for the behavioral sciences, L. Erlbaum Associates, 1988, ISBN 0-8058-0283-5, OCLC 17877467 .
JacobJ. Cohen JacobJ., A power primer., „Psychological Bulletin”, 112 (1), 1992, s. 155–159, DOI: 10.1037/0033-2909.112.1.155, ISSN 1939-1455 [dostęp 2017-01-31] (ang.).
Marcus R.M.R. Munafò Marcus R.M.R. i inni, Power failure: why small sample size undermines the reliability of neuroscience, „Nature Reviews Neuroscience”, 14 (5), 2013, s. 365–376, DOI: 10.1038/nrn3475, ISSN 1471-0048 [dostęp 2019-03-31] (ang.).
AndrewA. Gelman AndrewA., JohnJ. Carlin JohnJ., Beyond Power Calculations: Assessing Type S (Sign) and Type M (Magnitude) Errors, „Perspectives on Psychological Science”, 9 (6), 2014, s. 641–651, DOI: 10.1177/1745691614551642, ISSN 1745-6916 [dostęp 2019-03-31] (ang.).
Eric-JanE.J. Wagenmakers Eric-JanE.J. i inni, A power fallacy, „Behavior Research Methods”, 47 (4), 2015, s. 913–917, DOI: 10.3758/s13428-014-0517-4, ISSN 1554-3528 [dostęp 2019-03-31] (ang.).
DaniëlD. Lakens DaniëlD., Equivalence Tests: A Practical Primer for t Tests, Correlations, and Meta-Analyses, „Social Psychological and Personality Science”, 8 (4), 2017, s. 355–362, DOI: 10.1177/1948550617697177, ISSN 1948-5506, PMID: 28736600, PMCID: PMC5502906 [dostęp 2019-03-31] (ang.).
John MJ.M. Hoenig John MJ.M., Dennis MD.M. Heisey Dennis MD.M., The Abuse of Power: The Pervasive Fallacy of Power Calculations for Data Analysis, „The American Statistician”, 55 (1), 2001, s. 19–24, DOI: 10.1198/000313001300339897, ISSN 0003-1305 [dostęp 2019-03-31] (ang.).
JeehyoungJ. Kim JeehyoungJ., Bong SooB.S. Seo Bong SooB.S., How to Calculate Sample Size and Why, „Clinics in Orthopedic Surgery”, 5 (3), 2017, s. 235–242, DOI: 10.4055/cios.2013.5.3.235, ISSN 2005-291X, PMID: 24009911, PMCID: PMC3758995 [dostęp 2017-01-31] .
Helena ChmuraH.Ch. Kraemer Helena ChmuraH.Ch. i inni, Caution Regarding the Use of Pilot Studies to Guide Power Calculations for Study Proposals, „Archives of General Psychiatry”, 63 (5), 2006, DOI: 10.1001/archpsyc.63.5.484, ISSN 0003-990X [dostęp 2017-01-31] (ang.).
DaniëlD. Lakens DaniëlD., Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs, „Frontiers in Psychology”, 4, 2013, DOI: 10.3389/fpsyg.2013.00863, ISSN 1664-1078, PMID: 24324449, PMCID: PMC3840331 [dostęp 2017-01-31] .
David M.D.M. Erceg-Hurn David M.D.M., Vikki M.V.M. Mirosevich Vikki M.V.M., Modern robust statistical methods: an easy way to maximize the accuracy and power of your research, „The American Psychologist”, 63 (7), 2008, s. 591–601, DOI: 10.1037/0003-066X.63.7.591, ISSN 0003-066X, PMID: 18855490 [dostęp 2017-02-01] .
Jeffrey N.J.N. Rouder Jeffrey N.J.N., Julia M.J.M. Haaf Julia M.J.M., Power, Dominance, and Constraint: A Note on the Appeal of Different Design Traditions, „Advances in Methods and Practices in Psychological Science”, 1 (1), 2018, s. 19–26, DOI: 10.1177/2515245917745058, ISSN 2515-2459 [dostęp 2019-03-31] (ang.).
FranzF. Faul FranzF. i inni, Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses, „Behavior Research Methods”, 41 (4), 2009, s. 1149–1160, DOI: 10.3758/BRM.41.4.1149, ISSN 1554-3528 [dostęp 2019-03-31] (ang.).
Katherine S.K.S. Button Katherine S.K.S. i inni, Power failure: why small sample size undermines the reliability of neuroscience, „Nature Reviews Neuroscience”, 5, 2013, s. 365–376, DOI: 10.1038/nrn3475, ISSN 1471-003X [dostęp 2017-01-06] (ang.).
J.S.J.S. Rossi J.S.J.S., Statistical power of psychological research: what have we gained in 20 years?, „Journal of Consulting and Clinical Psychology”, 5, 1990, s. 646–656, ISSN 0022-006X, PMID: 2254513 [dostęp 2017-01-06] .
Frank A.F.A. Bosco Frank A.F.A. i inni, Correlational effect size benchmarks, „The Journal of Applied Psychology”, 2, 2015, s. 431–449, DOI: 10.1037/a0038047, ISSN 1939-1854, PMID: 25314367 [dostęp 2017-01-06] .
F.D.F.D. Richard F.D.F.D., Charles F.Ch.F. Bond Charles F.Ch.F., Juli J.J.J. Stokes-Zoota Juli J.J.J., One Hundred Years of Social Psychology Quantitatively Described., „Review of General Psychology”, 4, 2003, s. 331–363, DOI: 10.1037/1089-2680.7.4.331, ISSN 1939-1552 [dostęp 2017-01-06] .
T.D.T.D. Stanley T.D.T.D., Evan C.E.C. Carter Evan C.E.C., HristosH. Doucouliagos HristosH., What meta-analyses reveal about the replicability of psychological research., „Psychological Bulletin”, 144 (12), 2018, s. 1325–1346, DOI: 10.1037/bul0000169, ISSN 1939-1455 [dostęp 2019-03-31] (ang.).
John P.A.J.P.A. Ioannidis John P.A.J.P.A., Why most discovered true associations are inflated, „Epidemiology (Cambridge, Mass.)”, 5, 2008, s. 640–648, DOI: 10.1097/EDE.0b013e31818131e7, ISSN 1531-5487, PMID: 18633328 [dostęp 2017-01-06] .
John P.A.J.P.A. Ioannidis John P.A.J.P.A., Why Most Published Research Findings Are False, „PLOS Medicine”, 8, 2005, e124, DOI: 10.1371/journal.pmed.0020124, ISSN 1549-1676, PMID: 16060722, PMCID: PMC1182327 [dostęp 2017-01-06] .
Statistical methods in psychology journals: Guidelines and explanations., „American Psychologist”, 8, 1999, DOI: 10.1037/0003-066X.54.8.594, ISSN 1935-990X [dostęp 2017-01-06] .