Researchers can design a study to characterize a single instance of a phenomenon or to make an inference about a phenomenon in a population via a sample. Single-subject (or case) studies are justifiable when sampling is difficult or inappropriate. Psychosocial cases aimed at solving a specific problem usually require qualitative methods. Clinical cases are reports of diagnosis or treatment of injury or illness and are usually based on quantitative assessments and qualitative analysis. Non-clinical quantitative cases involve repeated sampling on a single subject and a quantitative inference about the subject generally. Sample-based designs are either observational or interventional, and most are aimed at quantifying a causal effect, in which changes in a predictor variable on average cause changes in a dependent variable. Establishing such causality in observational designs is problematic, owing to difficulties in adjusting for bias in the effect arising from confounders (variables that cause changes in the predictor and dependent). This problem is eliminated in interventions, but the necessary inclusion of a control treatment introduces bias mediated by differences between the groups in administration of treatments, compliance with study requirements, or imbalance in subject characteristics. Use of blinding and randomization at the design stage and inclusion of covariates in the analysis generally lead to trustworthy outcomes by reducing bias in interventions, but observational studies are sometimes the only ethically or logistically possible choice.
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