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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.
Quasi-experiments shares similarities with experiments or randomized controlled trials, but specifically lack random assignment to treatment or control. Instead, quasi-experimental designs typically allow assignment to treatment condition to proceed how it would in the absence of an experiment. [1]
The Solomon four-group design is a research method developed by Richard Solomon in 1949. [1] It is sometimes used in social science , psychology and medicine. It can be used if there are concerns that the treatment might be sensitized by the pre-test . [ 2 ]
The use of a sequence of experiments, where the design of each may depend on the results of previous experiments, including the possible decision to stop experimenting, is within the scope of sequential analysis, a field that was pioneered [12] by Abraham Wald in the context of sequential tests of statistical hypotheses. [13]
Interrupted time series design is the design of experiments based on the interrupted time series approach. The method is used in various areas of research, such as: political science : impact of changes in laws on the behavior of people; [ 2 ] (e.g., Effectiveness of sex offender registration policies in the United States )
Posttest probability = Posttest odds / (Posttest odds + 1) Fagan nomogram [ 3 ] The relation can also be estimated by a so-called Fagan nomogram (shown at right) by making a straight line from the point of the given pre-test probability to the given likelihood ratio in their scales, which, in turn, estimates the post-test probability at the ...
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).
The utilization of the between-group experimental design has several advantages. First, multiple variables, or multiple levels of a variable, can be tested simultaneously, and with enough testing subjects, a large number can be tested. Thus, the inquiry is broadened and extended beyond the effect of one variable (as with within-subject design).