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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. Observer-expectancy effect - Wikipedia

    en.wikipedia.org/wiki/Observer-expectancy_effect

    It is a significant threat to a study's internal validity, and is therefore typically controlled using a double-blind experimental design. It may include conscious or unconscious influences on subject behavior including creation of demand characteristics that influence subjects, and altered or selective recording of experimental results ...

  4. Confounding - Wikipedia

    en.wikipedia.org/wiki/Confounding

    The major threats to internal validity are history, maturation, testing, instrumentation, statistical regression, selection, experimental mortality, and selection-history interactions. One way to minimize the influence of artifacts is to use a pretest-posttest control group design.

  5. Member check - Wikipedia

    en.wikipedia.org/wiki/Member_check

    In qualitative research, a member check, also known as informant feedback or respondent validation, is a technique used by researchers to help improve the accuracy, credibility, validity, and transferability (also known as applicability, internal validity, [1] or fittingness) of a study. [2]

  6. Quasi-experiment - Wikipedia

    en.wikipedia.org/wiki/Quasi-experiment

    This is why validity is important for quasi experiments because they are all about causal relationships. It occurs when the experimenter tries to control all variables that could affect the results of the experiment. Statistical regression, history and the participants are all possible threats to internal validity.

  7. Multiple baseline design - Wikipedia

    en.wikipedia.org/wiki/Multiple_Baseline_Design

    This strategy is advantageous because it moderates several threats to validity, and history effects in particular. [2] [4] Concurrent multiple baseline designs are also useful for saving time, since all participants are processed at once. The ability to retrieve complete data sets within well defined time constraints is a valuable asset while ...

  8. Sports At Any Cost - projects.huffingtonpost.com

    projects.huffingtonpost.com/ncaa/sports-at-any...

    The HuffPost/Chronicle analysis found that subsidization rates tend to be highest at colleges where ticket sales and other revenue is the lowest — meaning that students who have the least interest in their college’s sports teams are often required to pay the most to support them.

  9. Control variable - Wikipedia

    en.wikipedia.org/wiki/Control_variable

    Confounding variables are a threat to the internal validity of an experiment. [5] [4] This situation may be resolved by first identifying the confounding variable and then redesigning the experiment taking that information into consideration. One way to this is to control the confounding variable, thus making it a control variable.