We provide a novel characterization of augmented balancing weights, also known as automatic debiased machine learning (AutoDML). These popular "doubly robust" or "de-biased machine learning estimators" combine outcome modeling with balancing weights -- weights that achieve covariate balance directly in lieu of estimating and…

Purpose: The lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size,…

Introduction: Concerns about the risk of bias (RoB) of Meta-analysis (MAs) have grown in parallel with the exponential increase in the number of publications in science. However, this has not been properly assessed in Education. The aims were to evaluate the RoB of MAs in Education and to identify potential predictors of a lower RoB. Methods:…

As traditionally conceived, publication bias arises from selection operating on a collection of individually unbiased estimates. A canonical form of such selection across studies (SAS) is the preferential publication of affirmative studies (i.e., those with significant, positive estimates) versus nonaffirmative studies (i.e., those with…

We conducted a multi-pronged investigation of different types of reporting bias in autism early childhood intervention research. First, we investigated the prevalence of reporting failures of completed trials registered on clinicaltrials.gov, and found that only 7% of registered trials were updated with results on the registration platform and…

Mixed research is a methodology of growing importance both within and without education. This type of research forces researchers to reconcile conflicting ways of justifying and understanding research with results that have the potential to be forward pointing for all researchers. As mixed research has grown, mixed research has gained an…

Numerous articles and textbooks advise qualitative researchers on accessing "hard-to-reach" or "hidden" populations. In this article, I compare two studies that I conducted with justice-involved women in the United States: a yearlong ethnography inside a state women's prison and an interview study with formerly incarcerated…

Evidence synthesis findings depend on the assumption that the included studies follow good clinical practice and results are not fabricated or false. Studies which are problematic due to scientific misconduct, poor research practice, or honest error may distort evidence synthesis findings. Authors of evidence synthesis need transparent mechanisms…

Background: Power analyses for a cluster-randomized trial (CRT) require estimates of additional design parameters beyond those needed for an individually randomized trial. In a 2-level CRT, there are two sample sizes, the number of clusters and the number of individuals per cluster. The intraclass correlation (ICC), or the proportion of variance…

Indirect questioning techniques such as the randomized response technique aim to control social desirability bias in surveys of sensitive topics. To improve upon previous indirect questioning techniques, we propose the new Cheating Detection Triangular Model. Similar to the Cheating Detection Model, it includes a mechanism for detecting…

Insufficient effort responding (IER) refers to a lack of effort when answering survey or questionnaire items. Such items typically offer more than two ordered response categories, with Likert-type scales as the most prominent example. The underlying assumption is that the successive categories reflect increasing levels of the latent variable…

The COVID-19 pandemic caused tremendous upheaval in schooling. In addition to devasting effects on students, these disruptions had consequences for researchers conducting studies on education programs and policies. Given the likelihood of future large-scale disruptions, it is important for researchers to plan resilient studies and think critically…

Background/Context: Confirmatory factor analysis (CFA) model is a commonly adopted framework to estimate and test a measurement model. Once a well-fitting final CFA model is selected, the selected model may be used to test structural relationships of the latent constructs with other variables, to construct a test with desired reliability and…

Partially specified correlation matrices (not to be confused with matrices with missing data or EM-correlation matrices) can appear in research settings such as integrative data analyses, quantitative systematic reviews or whenever the study design only allows for the collection of certain variables. Although approaches to fill in these missing…

Imputation or likelihood-based approaches to handle missing data assume the data are missing completely at random (MCAR) or missing at random (MAR). However, little research has examined the missingness pattern before using these imputation/likelihood methods. Three missingness mechanisms -- MCAR, MAR, and not missing at random (NMAR) -- can be…