Warning: Undefined array key "mm" in /www/wwwroot/www.ai-bt.com/si.php on line 10 Deprecated: trim(): Passing null to parameter #1 ($string) of type string is deprecated in /www/wwwroot/www.ai-bt.com/si.php on line 10 A Very Short List of Common Pitfalls in Research Design, Data Analysis, and Reporting.

Literature DB >> 36119906

A Very Short List of Common Pitfalls in Research Design, Data Analysis, and Reporting.

Maarten van Smeden¹.

Abstract

Entities: Chemical

Year: 2022 PMID： 36119906 PMCID： PMC9477699 DOI： 10.22454/PRiMER.2022.511416

Source DB: PubMed Journal: PRiMER ISSN： 2575-7873

Keyword Cloud
References

× No keyword cloud information.

27 in total

1. What you see may not be what you get: a brief, nontechnical introduction to overfitting in regression-type models.

Authors: Michael A Babyak
Journal: Psychosom Med Date: 2004 May-Jun Impact factor: 4.312

Review 2. An introduction to causal inference.

Authors: Judea Pearl
Journal: Int J Biostat Date: 2010-02-26 Impact factor: 0.968

Review 3. Mediation Analysis: A Practitioner's Guide.

Authors: Tyler J VanderWeele
Journal: Annu Rev Public Health Date: 2015-11-30 Impact factor: 21.981

Review 4. STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 1-Basic theory and simple methods of adjustment.

Authors: Ruth H Keogh; Pamela A Shaw; Paul Gustafson; Raymond J Carroll; Veronika Deffner; Kevin W Dodd; Helmut Küchenhoff; Janet A Tooze; Michael P Wallace; Victor Kipnis; Laurence S Freedman
Journal: Stat Med Date: 2020-04-03 Impact factor: 2.373

5. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls.

Authors: Jonathan A C Sterne; Ian R White; John B Carlin; Michael Spratt; Patrick Royston; Michael G Kenward; Angela M Wood; James R Carpenter
Journal: BMJ Date: 2009-06-29

6. Causal analyses of existing databases: the importance of understanding what can be achieved with your data before analysis (commentary on Hernán).

Authors: Tim P Morris; Maarten van Smeden
Journal: J Clin Epidemiol Date: 2021-09-22 Impact factor: 6.437

A Very Short List of Common Pitfalls in Research Design, Data Analysis, and Reporting.

1. What you see may not be what you get: a brief, nontechnical introduction to overfitting in regression-type models.

Review 2. An introduction to causal inference.

Review 3. Mediation Analysis: A Practitioner's Guide.

Review 4. STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 1-Basic theory and simple methods of adjustment.

5. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls.

6. Causal analyses of existing databases: the importance of understanding what can be achieved with your data before analysis (commentary on Hernán).

7. No rationale for 1 variable per 10 events criterion for binary logistic regression analysis.

Review 8. A review of spline function procedures in R.

9. Accounting for missing data in statistical analyses: multiple imputation is not always the answer.

10. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations.