TL;DR: In this article, the authors present experiments and generalized Causal inference methods for single and multiple studies, using both control groups and pretest observations on the outcome of the experiment, and a critical assessment of their assumptions.
Abstract: 1. Experiments and Generalized Causal Inference 2. Statistical Conclusion Validity and Internal Validity 3. Construct Validity and External Validity 4. Quasi-Experimental Designs That Either Lack a Control Group or Lack Pretest Observations on the Outcome 5. Quasi-Experimental Designs That Use Both Control Groups and Pretests 6. Quasi-Experimentation: Interrupted Time Series Designs 7. Regression Discontinuity Designs 8. Randomized Experiments: Rationale, Designs, and Conditions Conducive to Doing Them 9. Practical Problems 1: Ethics, Participant Recruitment, and Random Assignment 10. Practical Problems 2: Treatment Implementation and Attrition 11. Generalized Causal Inference: A Grounded Theory 12. Generalized Causal Inference: Methods for Single Studies 13. Generalized Causal Inference: Methods for Multiple Studies 14. A Critical Assessment of Our Assumptions
TL;DR: It is shown that it is feasible to develop a checklist that can be used to assess the methodological quality not only of randomised controlled trials but also non-randomised studies and it is possible to produce a Checklist that provides a profile of the paper, alerting reviewers to its particular methodological strengths and weaknesses.
Abstract: OBJECTIVE: To test the feasibility of creating a valid and reliable checklist with the following features: appropriate for assessing both randomised and non-randomised studies; provision of both an overall score for study quality and a profile of scores not only for the quality of reporting, internal validity (bias and confounding) and power, but also for external validity. DESIGN: A pilot version was first developed, based on epidemiological principles, reviews, and existing checklists for randomised studies. Face and content validity were assessed by three experienced reviewers and reliability was determined using two raters assessing 10 randomised and 10 non-randomised studies. Using different raters, the checklist was revised and tested for internal consistency (Kuder-Richardson 20), test-retest and inter-rater reliability (Spearman correlation coefficient and sign rank test; kappa statistics), criterion validity, and respondent burden. MAIN RESULTS: The performance of the checklist improved considerably after revision of a pilot version. The Quality Index had high internal consistency (KR-20: 0.89) as did the subscales apart from external validity (KR-20: 0.54). Test-retest (r 0.88) and inter-rater (r 0.75) reliability of the Quality Index were good. Reliability of the subscales varied from good (bias) to poor (external validity). The Quality Index correlated highly with an existing, established instrument for assessing randomised studies (r 0.90). There was little difference between its performance with non-randomised and with randomised studies. Raters took about 20 minutes to assess each paper (range 10 to 45 minutes). CONCLUSIONS: This study has shown that it is feasible to develop a checklist that can be used to assess the methodological quality not only of randomised controlled trials but also non-randomised studies. It has also shown that it is possible to produce a checklist that provides a profile of the paper, alerting reviewers to its particular methodological strengths and weaknesses. Further work is required to improve the checklist and the training of raters in the assessment of external validity.
TL;DR: The use of reliability and validity are common in quantitative research and now it is reconsidered in the qualitative research paradigm as discussed by the authors, which can also illuminate some ways to test or maximize the validity and reliability of a qualitative study.
Abstract: The use of reliability and validity are common in quantitative research and now it is reconsidered in the qualitative research paradigm. Since reliability and validity are rooted in positivist perspective then they should be redefined for their use in a naturalistic approach. Like reliability and validity as used in quantitative research are providing springboard to examine what these two terms mean in the qualitative research paradigm, triangulation as used in quantitative research to test the reliability and validity can also illuminate some ways to test or maximize the validity and reliability of a qualitative study. Therefore, reliability, validity and triangulation, if they are relevant research concepts, particularly from a qualitative point of view, have to be redefined in order to reflect the multiple ways of establishing truth. Key words: Reliability, Validity, Triangulation, Construct, Qualitative, and Quantitative This article discusses the use of reliability and validity in the qualitative research paradigm. First, the meanings of quantitative and qualitative research are discussed. Secondly, reliability and validity as used in quantitative research are discussed as a way of providing a springboard to examining what these two terms mean and how they can be tested in the qualitative research paradigm. This paper concludes by drawing upon the use of triangulation in the two paradigms (quantitative and qualitative) to show how the changes have influenced our understanding of reliability, validity and triangulation in qualitative studies.
TL;DR: The aim of the present study was to develop and validate an instrument that can be used to determine the methodological quality of observational or non‐randomized studies in surgical research.
Abstract: Background: Because of specific methodological difficulties in conducting randomized trials, surgical research remains dependent predominantly on observational or non-randomized studies. Few validated instruments are available to determine the methodological quality of such studies either from the reader's perspective or for the purpose of meta-analysis. The aim of the present study was to develop and validate such an instrument.
Methods: After an initial conceptualization phase of a methodological index for non-randomized studies (MINORS), a list of 12 potential items was sent to 100 experts from different surgical specialities for evaluation and was also assessed by 10 clinical methodologists. Subsequent testing involved the assessment of inter-reviewer agreement, test-retest reliability at 2 months, internal consistency reliability and external validity.
Results: The final version of MINORS contained 12 items, the first eight being specifically for non-comparative studies. Reliability was established on the basis of good inter-reviewer agreement, high test-retest reliability by the κ-coefficient and good internal consistency by a high Cronbach's α-coefficient. External validity was established in terms of the ability of MINORS to identify excellent trials.
Conclusions: MINORS is a valid instrument designed to assess the methodological quality of non-randomized surgical studies, whether comparative or non-comparative. The next step will be to determine its external validity when used in a large number of studies and to compare it with other existing instruments.