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  2. Internal validity - Wikipedia

    en.wikipedia.org/wiki/Internal_validity

    Internal validity, therefore, is more a matter of degree than of either-or, and that is exactly why research designs other than true experiments may also yield results with a high degree of internal validity. In order to allow for inferences with a high degree of internal validity, precautions may be taken during the design of the study.

  3. Validity (statistics) - Wikipedia

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

    Internal validity is an inductive estimate of the degree to which conclusions about causal relationships can be made (e.g. cause and effect), based on the measures used, the research setting, and the whole research design. Good experimental techniques, in which the effect of an independent variable on a dependent variable is studied under ...

  4. Design of experiments - Wikipedia

    en.wikipedia.org/wiki/Design_of_experiments

    Main concerns in experimental design include the establishment of validity, reliability, and replicability. For example, these concerns can be partially addressed by carefully choosing the independent variable, reducing the risk of measurement error, and ensuring that the documentation of the method is sufficiently detailed.

  5. Multitrait-multimethod matrix - Wikipedia

    en.wikipedia.org/wiki/Multitrait-multimethod_matrix

    The multitrait-multimethod (MTMM) matrix is an approach to examining construct validity developed by Campbell and Fiske (1959). [1] It organizes convergent and discriminant validity evidence for comparison of how a measure relates to other measures. The conceptual approach has influenced experimental design and measurement theory in psychology ...

  6. Replication (statistics) - Wikipedia

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

    In engineering, science, and statistics, replication is the process of repeating a study or experiment under the same or similar conditions. It is a crucial step to test the original claim and confirm or reject the accuracy of results as well as for identifying and correcting the flaws in the original experiment. [1]

  7. 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.

  8. Field experiment - Wikipedia

    en.wikipedia.org/wiki/Field_experiment

    This increases the speed and efficiency of gathering experimental results and reduces the costs of implementing the experiment. Another cutting-edge technique in field experiments is the use of the multi armed bandit design, [ 11 ] including similar adaptive designs on experiments with variable outcomes and variable treatments over time.

  9. Optimal experimental design - Wikipedia

    en.wikipedia.org/wiki/Optimal_experimental_design

    In the design of experiments, optimal experimental designs (or optimum designs [2]) are a class of experimental designs that are optimal with respect to some statistical criterion. The creation of this field of statistics has been credited to Danish statistician Kirstine Smith .