Het kwantitatief integreren van empirische studies: de methode van meta-analyse

2006 ◽  
Vol 19 (3) ◽  
Author(s):  
Marise Ph. Born ◽  
Stefan T. Mol
Keyword(s):  
Meta Analysis ◽  
Research Question ◽  
Empirical Studies ◽  
Dominant Position ◽  
The Social ◽  
Research Findings ◽  
The Many ◽  
Quantitative Integration ◽  
Meta Analyses ◽  
Research Domain

Quantitatively integrating empirical studies: The method of meta-analysis Quantitatively integrating empirical studies: The method of meta-analysis Marise Ph. Born & Stefan T. Mol, Gedrag & Organisatie, Volume 19, September 2006, nr. 3, pp. 251-271 Meta-analysis is a quantitative integration of results of a series of empirical studies into a specific research question. The method of meta-analysis has obtained a dominant position in the social sciences and beyond, as it may help in obtaining an overview of the explosively increased number of research publications. This contribution discusses the basics and consecutive steps in performing a meta-analysis. A meta-analysis that we conducted on expatriates serves as an illustration. Next to the many points in favor of meta-analyses, such as having a better overview of a research domain and shifting the traditional focus on significances of effects to sizes of effects, several important controversies remain. One of these is the issue of waving away a specific cause of variance in research findings as a methodological artifact, or interpreting it as a meaningful case of variance. We maintain that every social or industrial- and organizational psychologist who wants to stay up-to-date scientifically should be able to interpret meta-analyses.

Transparency of reporting in CALL meta-analyses between 2003 and 2015

ReCALL ◽  
2017 ◽  
Vol 30 (3) ◽  
pp. 253-277 ◽  
Author(s):  
Huifen Lin ◽  
Tsuiping Chen ◽  
Hsien-Chin Liou
Keyword(s):  
Language Learning ◽  
Meta Analysis ◽  
Empirical Studies ◽  
Research Synthesis ◽  
Computer Assisted ◽  
Computer Assisted Language Learning ◽  
Conducting Research ◽  
Number Of Publications ◽  
Meta Analyses ◽  
Research Domain

AbstractSince its introduction by Glass in the 1970s, meta-analysis has become a widely accepted and the most preferred approach to conducting research synthesis. Overcoming the weaknesses commonly associated with traditional narrative review and vote counting, meta-analysis is a statistical method of systematically aggregating and analyzing empirical studies by following well-established procedures. The findings of a meta-analysis, when appropriately conducted, are able to inform important policy decisions and provide practical pedagogical suggestions. With the growing number of publications employing meta-analysis across a wide variety of disciplines, it has received criticism due to its inconsistent findings derived from multiple meta-analyses in the same research domain. These inconsistencies have arisen partly due to the alternatives available to meta-analysts in each major meta-analytic procedure. Researchers have therefore recommended transparent reporting on the decision-making for every essential judgment call so that the results across multiple meta-analyses become replicable, consistent, and interpretable. This research explored the degree to which meta-analyses in the computer-assisted language learning (CALL) discipline transparently reported their decisions in every critical step. To achieve this aim, we retrieved 15 eligible meta-analyses in CALL published between 2003 and 2015. Features of these meta-analyses were extracted based on a codebook modified from Cooper (2003) and Aytug, Rothstein, Zhou and Kern (2012). A transparency score of reporting was then calculated to examine the degree to which these meta-analyses are compliant with the norms of reporting as recommended in the literature. We then discuss the strengths and weaknesses of the methodologies and provide suggestions for conducting quality meta-analyses in this domain.

The Identification and Prevention of Publication Bias in the Social Sciences and Economics

2011 ◽  
Vol 231 (5-6) ◽  
Author(s):  
Bernd Weiß ◽  
Michael Wagner
Keyword(s):  
Social Sciences ◽  
Missing Data ◽  
Publication Bias ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Empirical Studies ◽  
Systematic Research ◽  
Research Results ◽  
The Social ◽  
Research Findings

SummarySystematic research reviews have become essential in all empirical sciences. However, the validity of research syntheses is threatened by the fact that not all studies on a given topic can be summarized. Research reviews may suffer from missing data, and this is especially crucial in those cases where the selectivity of studies and their findings affects the summarized result. So-called publication bias is a type of missing data and a phenomenon that jeopardizes the validity of systematic or quantitative, as well as narrative, reviews. Publication bias exists if the preparation, submission or publication of research findings depend on characteristics of just these research results, e. g. their direction or statistical significance. This article describes methods to identify publication bias in the context of meta-analysis. It also reviews empirical studies on the prevalence of publication bias, especially in the social and economic sciences, where publication bias also seems to be prevalent. Several proposals to prevent publication bias are discussed.

scholarly journals Has the Credibility of the Social Sciences Been Credibly Destroyed? Reanalyzing the “Many Analysts, One Data Set” Project

2021 ◽  
Vol 7 ◽  
pp. 237802312110244
Author(s):  
Katrin Auspurg ◽  
Josef Brüderl
Keyword(s):  
Social Sciences ◽  
Causal Reasoning ◽  
Research Question ◽  
Social Science Research ◽  
Science Research ◽  
Skin Tone ◽  
Data Set ◽  
The Social ◽  
The Many ◽  
Definition Of

In 2018, Silberzahn, Uhlmann, Nosek, and colleagues published an article in which 29 teams analyzed the same research question with the same data: Are soccer referees more likely to give red cards to players with dark skin tone than light skin tone? The results obtained by the teams differed extensively. Many concluded from this widely noted exercise that the social sciences are not rigorous enough to provide definitive answers. In this article, we investigate why results diverged so much. We argue that the main reason was an unclear research question: Teams differed in their interpretation of the research question and therefore used diverse research designs and model specifications. We show by reanalyzing the data that with a clear research question, a precise definition of the parameter of interest, and theory-guided causal reasoning, results vary only within a narrow range. The broad conclusion of our reanalysis is that social science research needs to be more precise in its “estimands” to become credible.

scholarly journals Are you really using Yarning research? Mapping Social and Family Yarning to strengthen Yarning research quality

2021 ◽  
pp. 117718012110154
Author(s):  
Petah Atkinson ◽  
Marilyn Baird ◽  
Karen Adams
Keyword(s):  
Research Method ◽  
Research Question ◽  
Research Quality ◽  
Aboriginal Community ◽  
Participant Recruitment ◽  
The Social ◽  
Research Findings ◽  
Convenience Sampling ◽  
Missing Feature ◽  
Published Research

Yarning as a research method has its grounding as an Aboriginal culturally specified process. Significant to the Research Yarn is relationality, however; this is a missing feature of published research findings. This article aims to address this. The research question was, what can an analysis of Social and Family Yarning tell us about relationality that underpins a Research Yarn. Participant recruitment occurred using convenience sampling, and data collection involved Yarning method. Five steps of data analysis occurred featuring Collaborative Yarning and Mapping. Commonality existed between researcher and participants through predominantly experiences of being a part of Aboriginal community, via Aboriginal organisations and Country. This suggests shared explicit and tacit knowledge and generation of thick data. Researchers should report on their experience with Yarning, the types of Yarning they are using, and the relationality generated from the Social, Family and Research Yarn.

scholarly journals Comparative Effectiveness Research: Using Systematic Reviews and Meta-Analyses to Synthesize Empirical Evidence

2011 ◽  
Vol 25 (3) ◽  
pp. 191-209 ◽  
Author(s):  
Maria C. Katapodi ◽  
Laurel L. Northouse
Keyword(s):  
Systematic Reviews ◽  
Comparative Effectiveness Research ◽  
Comparative Effectiveness ◽  
Meta Analysis ◽  
Research Question ◽  
Alternative Methods ◽  
Evidence Based ◽  
Effectiveness Research ◽  
Meta Analyses ◽  
Research Studies

The increased demand for evidence-based health care practices calls for comparative effectiveness research (CER), namely the generation and synthesis of research evidence to compare the benefits and harms of alternative methods of care. A significant contribution of CER is the systematic identification and synthesis of available research studies on a specific topic. The purpose of this article is to provide an overview of methodological issues pertaining to systematic reviews and meta-analyses to be used by investigators with the purpose of conducting CER. A systematic review or meta-analysis is guided by a research protocol, which includes (a) the research question, (b) inclusion and exclusion criteria with respect to the target population and studies, © guidelines for obtaining relevant studies, (d) methods for data extraction and coding, (e) methods for data synthesis, and (f ) guidelines for reporting results and assessing for bias. This article presents an algorithm for generating evidence-based knowledge by systematically identifying, retrieving, and synthesizing large bodies of research studies. Recommendations for evaluating the strength of evidence, interpreting findings, and discussing clinical applicability are offered.

118 The Use of Meta-analysis in Companion Animal Research

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 62-62
Author(s):  
Emma N Bermingham
Keyword(s):  
Body Size ◽  
Statistical Analysis ◽  
Meta Analysis ◽  
Energy Requirements ◽  
Specific Question ◽  
Research Findings ◽  
Adult Cat ◽  
Number Of Publications ◽  
Meta Analyses ◽  
The Three Rs

Abstract In a world of the “Three Rs” (replace, reduce and refine), combined with more research published via open access research journals, there is increasing interest in the statistical analysis of existing literature. Meta-analysis – the combination of multiple studies, can be used to get better oversight into a specific question of interest. Additionally, it can be used to identify gaps in knowledge. For example, while there are a number of publications investigating energy requirements in adult cat and dog, few studies assess older animals. Similarly, in the dog, there is a lack of literature around dogs at the extremes of body size (i.e. giant and toy breeds). Herein, we describe several published examples that have been used to determine energy requirements of cats and dogs, and more recently, the impacts of diet on the microbiome of the cat and dog. This includes the use of Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, research findings and general findings related to research design and quality.

Socioeconomic Status and Academic Outcomes in Developing Countries: A Meta-Analysis

2019 ◽  
Vol 89 (6) ◽  
pp. 875-916 ◽  
Author(s):  
Sung won Kim ◽  
Hyunsun Cho ◽  
Lois Y. Kim
Keyword(s):  
Socioeconomic Status ◽  
Developing Countries ◽  
Academic Outcomes ◽  
Meta Analysis ◽  
Empirical Studies ◽  
Developed Countries ◽  
Industrialized Countries ◽  
And Gender ◽  
Meta Analyses ◽  
K 12

Despite the multiple meta-analyses documenting the association between socioeconomic status (SES) and achievement, none have examined this question outside of English-speaking industrialized countries. This study is the first meta-analytic effort, to the best of our knowledge, to focus on developing countries. Based on 49 empirical studies representing 38 countries, and a sample of 2,828,216 school-age students (grades K–12) published between 1990 and 2017, we found an overall weak relation between SES and academic outcomes. Results for attainment outcomes were stronger than achievement outcomes, and the effect size was stronger in more economically developed countries. The SES-academic outcome relation was further moderated by grade level and gender. There were no differences in the strength of the relation by specific SES measures of income/consumption, education, and wealth/home resources. Our results provide evidence that educational inequalities are wider in higher income countries, creating a serious challenge for developing countries as they expand school access.

scholarly journals Global, regional and national estimates ofToxoplasma gondiiseroprevalence in pregnant women: a protocol for a systematic review and modelling analysis

BMJ Open ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. e030472 ◽  
Author(s):  
Jean Joel Bigna ◽  
Joel Noutakdie Tochie ◽  
Dahlia Noelle Tounouga ◽  
Anne Olive Bekolo ◽  
Nadia S Ymele ◽  
...  
Keyword(s):  
Public Health ◽  
Toxoplasma Gondii ◽  
Pregnant Women ◽  
Data Extraction ◽  
Meta Analysis ◽  
Empirical Studies ◽  
Published Data ◽  
Representative Study ◽  
Nationally Representative ◽  
Meta Analyses

IntroductionTo set priorities for public health policy, funding for public health interventions, and healthcare planning which will ultimately contribute in bending the burden of toxoplasmosis towards maternal and neonatal health, it is necessary to have accurate data on the prevalence of toxoplasmosis in pregnancy. Therefore, we aimed to estimate the seroprevalence ofToxoplasma gondiiinfection in pregnant women by countries, WHO regions and globally.Methods and analysisWe will search multiple databases to identify studies that reported the prevalence (or enough data to compute this estimate) ofToxoplasma gondiiin the global population of pregnant women up till December 31, 2018 without any language restrictions. Study selection, data extraction and risk of bias assessment will be conducted independently by three pairs of investigators. For each country, we will estimate the prevalence based on empirical studies if there is either one nationally representative study, or two or more not nationally representative studies. Then, we will perform a country-specific random-effects meta-analyses. The heterogeneity will be evaluated using the χ² test on Cochrane’s Q statistic and quantified with H and I² statistics. For countries with one or no empirical studies or where the meta-analysis will result in a wide CI of 0%–100%, we will predict the country’s prevalence by using a Bayesian generalised non-linear multilevel model. The model will have a hierarchical structure in which estimates for each country will be informed by its own data, if available, or by data from other countries in the same WHO region.Ethics and disseminationSince this study will be based on published data, it does not require any ethical approval. Its findings will be published in a scientific peer-reviewed journal. They will also be presented at scientific conferences and to relevant public health sectors.PROSPERO registration numberCRD42019125572.

Meta-Analyses as a Multi-Level Model

2019 ◽  
pp. 109442811985747
Author(s):  
Janaki Gooty ◽  
George C. Banks ◽  
Andrew C. Loignon ◽  
Scott Tonidandel ◽  
Courtney E. Williams
Keyword(s):  
Educational Psychology ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Independence Assumption ◽  
The Social ◽  
Level Model ◽  
Multi Level ◽  
Meta Analyses ◽  
User Friendly ◽  
Organizational Sciences

Meta-analyses are well known and widely implemented in almost every domain of research in management as well as the social, medical, and behavioral sciences. While this technique is useful for determining validity coefficients (i.e., effect sizes), meta-analyses are predicated on the assumption of independence of primary effect sizes, which might be routinely violated in the organizational sciences. Here, we discuss the implications of violating the independence assumption and demonstrate how meta-analysis could be cast as a multilevel, variance known (Vknown) model to account for such dependency in primary studies’ effect sizes. We illustrate such techniques for meta-analytic data via the HLM 7.0 software as it remains the most widely used multilevel analyses software in management. In so doing, we draw on examples in educational psychology (where such techniques were first developed), organizational sciences, and a Monte Carlo simulation (Appendix). We conclude with a discussion of implications, caveats, and future extensions. Our Appendix details features of a newly developed application that is free (based on R), user-friendly, and provides an alternative to the HLM program.

Weight- and meta-analysis of empirical literature on entrepreneurship

2017 ◽  
Vol 18 (3) ◽  
pp. 195-209 ◽  
Author(s):  
Adel Alferaih
Keyword(s):  
Empirical Research ◽  
Meta Analysis ◽  
Empirical Studies ◽  
Entrepreneurial Intentions ◽  
Empirical Literature ◽  
Research Model ◽  
Entrepreneurship Research ◽  
Meta Analyses

While a number of studies have reviewed empirical research on individuals’ entrepreneurial intentions (EIs), very little is known about the cumulative performance of frequently used constructs and their direct and indirect relationships with EI. This research has exposed 123 usable empirical studies of EI to weight- and meta-analyses to determine the cumulative performance of various frequently explored relationships. A generic research model of the antecedents of EI is proposed on that basis. The outcomes of this research and its limitations have practical and theoretical implications for future entrepreneurship research.

Sign in / Sign up

Export Citation Format

Share Document