3.2 Statistical models for aggregate data.Here it is convenient to follow the terminology used by the Cochrane Collaboration, and use "meta-analysis" to refer to statistical methods of combining evidence, leaving other aspects of ' research synthesis' or 'evidence synthesis', such as combining information from qualitative studies, for the more general context of systematic reviews. For instance, a meta-analysis may be conducted on several clinical trials of a medical treatment, in an effort to obtain a better understanding of how well the treatment works. Meta-analyses are often, but not always, important components of a systematic review procedure. For example, Wanous and colleagues examined four pairs of meta-analyses on the four topics of (a) job performance and satisfaction relationship, (b) realistic job previews, (c) correlates of role conflict and ambiguity, and (d) the job satisfaction and absenteeism relationship, and illustrated how various judgement calls made by the researchers produced different results. Judgment calls made in completing a meta-analysis may affect the results.
However, in performing a meta-analysis, an investigator must make choices which can affect the results, including deciding how to search for studies, selecting studies based on a set of objective criteria, dealing with incomplete data, analyzing the data, and accounting for or choosing not to account for publication bias. Not only can meta-analyses provide an estimate of the unknown common truth, it also has the capacity to contrast results from different studies and identify patterns among study results, sources of disagreement among those results, or other interesting relationships that may come to light with multiple studies. The aim then is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived. Meta-analyses can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error. As a group of social science PhD students from U21 universities, we are launching a Social Sciences Online Writing Workshop to self-empower ourselves by innovatively refreshing research skills and writing collaboratively and inter-disciplinarily.A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. The cessation of travel opportunities brought by international or domestic travel bans and limitations has forced many researchers to either change, postpone, or even cancel their original research plans. Humanities and social sciences, relying heavily on fieldwork for data collection, are particularly hit hard by the pandemic. His publications have appeared in Applied Linguistics, International Review of Applied Linguistics, Language Learning, Language Teaching Research, Modern Language Journal, Studies in Second Language Acquisition, System, among others.ĬOVID-19 is fundamentally changing academic research landscape. cognitive aptitudes) factors on second language learning outcomes. His research has primarily focused on the joint effects of learner-external (e.g. Li’s main research interests include language aptitude, working memory, form-focused instruction, task-based language teaching and learning, corrective feedback, and research methods (including meta-analysis). Shaofeng Li is an Associate Professor of Second and Foreign Language Education at Florida State University. He will also address topics that have received little attention in methodological and statistical guides such as literature review and meta-analysis. He will discuss key statistical analyses utilized in correlational and experimental studies, which roughly correspond to analyses involving covariance and mean difference respectively. Li will clarify issues and judgment calls at each stage of a quantitative study and make recommendations on how to address related issues. Drawing on his expertise in research methods and rich experience in conducting different types of quantitative research, Dr. This talk provides an introductory, practical, and comprehensive guide to the steps involved in carrying out a quantitative study, including problem formulation, literature review, research methods, data analysis, result reporting, and discussion. Quantitative research seeks to draw on numerical data to explore the occurrence of events, the relationship between phenomena, and the effects of systematic interventions on related outcomes.