Sampling in developmental science: Situations, shortcomings, solutions, and standards

• Sampling is a key feature of every study in developmental science.
• We evaluate four prominent sampling strategies in developmental science.
• We judge these sampling strategies by criteria, such as representativeness and generalizability.
• We tally the use of the four sampling strategies in five prominent developmental science journals.
• Finally, we make recommendations about best practices for sample selection and reporting.

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.