Sampling in developmental science: Situations,shortcomings, solutions,and standards |
| |
| Institution: | 1. Centre for Coevolution of Biology & Culture, Department of Psychology, Durham University, DH1 3LE, UK;2. Centre for Coevolution of Biology & Culture, Department of Anthropology, Durham University, Durham DH1 3LE, UK;3. Centre for Coevolution of Biology & Culture, School of Education, Durham University, Durham DH1 1TA, UK;1. Department of Psychology, University of Copenhagen, Denmark;2. Institute for Advanced Studies in the Humanities & Perception Movement Action Research Consortium, University of Edinburgh, UK;3. Faculty of Humanities & Social Sciences, University of Strathclyde, UK;4. Center for Mind, Brain and Cognitive Evolution, Institut für Philosophie II, Ruhr Universität Bochum, Germany;1. Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH;2. Department of Respiratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China;1. Hubert Department of Global Health, Rollins School of Public Health, Emory University, 1518 Clifton Rd, Atlanta, GA, 30322, USA;2. Department of Anthropology and Global Health Program, University of California San Diego, 9500 Gilman Drive 0532, La Jolla, CA, 92093, USA |
| |
| Abstract: | Sampling is a key feature of every study in developmental science. Although sampling has far-reaching implications, too little attention is paid to sampling. Here, we describe, discuss, and evaluate four prominent sampling strategies in developmental science: population-based probability sampling, convenience sampling, quota sampling, and homogeneous sampling. We then judge these sampling strategies by five criteria: whether they yield representative and generalizable estimates of a study’s target population, whether they yield representative and generalizable estimates of subsamples within a study’s target population, the recruitment efforts and costs they entail, whether they yield sufficient power to detect subsample differences, and whether they introduce “noise” related to variation in subsamples and whether that “noise” can be accounted for statistically. We use sample composition of gender, ethnicity, and socioeconomic status to illustrate and assess the four sampling strategies. Finally, we tally the use of the four sampling strategies in five prominent developmental science journals and make recommendations about best practices for sample selection and reporting. |
| |
| Keywords: | Sampling Methodology Developmental science |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
