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  2. Quasi-experiment - Wikipedia

    en.wikipedia.org/wiki/Quasi-experiment

    The lack of random assignment in the quasi-experimental design method may allow studies to be more feasible, but this also poses many challenges for the investigator in terms of internal validity. This deficiency in randomization makes it harder to rule out confounding variables and introduces new threats to internal validity . [ 11 ]

  3. Regression discontinuity design - Wikipedia

    en.wikipedia.org/wiki/Regression_discontinuity...

    In statistics, econometrics, political science, epidemiology, and related disciplines, a regression discontinuity design (RDD) is a quasi-experimental pretest–posttest design that aims to determine the causal effects of interventions by assigning a cutoff or threshold above or below which an intervention is assigned.

  4. Design of experiments - Wikipedia

    en.wikipedia.org/wiki/Design_of_experiments

    One of the most important requirements of experimental research designs is the necessity of eliminating the effects of spurious, intervening, and antecedent variables. In the most basic model, cause (X) leads to effect (Y). But there could be a third variable (Z) that influences (Y), and X might not be the true cause at all.

  5. Interrupted time series - Wikipedia

    en.wikipedia.org/wiki/Interrupted_time_series

    Interrupted time series analysis (ITS), sometimes known as quasi-experimental time series analysis, is a method of statistical analysis involving tracking a long-term period before and after a point of intervention to assess the intervention's effects.

  6. Matching (statistics) - Wikipedia

    en.wikipedia.org/wiki/Matching_(statistics)

    Matching is a statistical technique that evaluates the effect of a treatment by comparing the treated and the non-treated units in an observational study or quasi-experiment (i.e. when the treatment is not randomly assigned).

  7. Impact evaluation - Wikipedia

    en.wikipedia.org/wiki/Impact_evaluation

    Impact evaluation designs are identified by the type of methods used to generate the counterfactual and can be broadly classified into three categories – experimental, quasi-experimental and non-experimental designs – that vary in feasibility, cost, involvement during design or after implementation phase of the intervention, and degree of ...

  8. Experimental data - Wikipedia

    en.wikipedia.org/wiki/Experimental_data

    Experimental data in science and engineering is data produced by a measurement, test method, experimental design or quasi-experimental design. In clinical research any data produced are the result of a clinical trial. Experimental data may be qualitative or quantitative, each being appropriate for different investigations.

  9. Multiple baseline design - Wikipedia

    en.wikipedia.org/wiki/Multiple_Baseline_Design

    Ex post facto recruitment methods are not considered true experiments, due to the limits of experimental control or randomized control that the experimenter has over the trait. This is because a control group may necessarily be selected from a discrete separate population. This research design is thus considered a quasi-experimental design.