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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. Quasi-empirical method - Wikipedia

    en.wikipedia.org/wiki/Quasi-empirical_method

    Quasi-empirical methods aim to be as closely analogous to empirical methods as possible. [ 1 ] Empirical research relies on, and its empirical methods involve experimentation and disclosure of apparatus for reproducibility , by which scientific findings are validated by other scientists.

  4. Regression discontinuity design - Wikipedia

    en.wikipedia.org/.../Regression_discontinuity_design

    The RD design takes the shape of a quasi-experimental research design with a clear structure that is devoid of randomized experimental features. Several aspects deny the RD designs an allowance for a status quo. For instance, the designs often involve serious issues that do not offer room for random experiments.

  5. 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).

  6. Design of experiments - Wikipedia

    en.wikipedia.org/wiki/Design_of_experiments

    As with other branches of statistics, experimental design is pursued using both frequentist and Bayesian approaches: In evaluating statistical procedures like experimental designs, frequentist statistics studies the sampling distribution while Bayesian statistics updates a probability distribution on the parameter space.

  7. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined based on the cost, time, or convenience of collecting the data, and the need for it to offer sufficient statistical power. In complex studies ...

  8. Clinical study design - Wikipedia

    en.wikipedia.org/wiki/Clinical_study_design

    Randomized controlled trial [5]. Blind trial [6]; Non-blind trial [7]; Adaptive clinical trial [8]. Platform Trials; Nonrandomized trial (quasi-experiment) [9]. Interrupted time series design [10] (measures on a sample or a series of samples from the same population are obtained several times before and after a manipulated event or a naturally occurring event) - considered a type of quasi ...

  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.