Convergent validity Discriminant validity I have to warn you here that I made this list up. First, as mentioned above, I would like to use the term construct validity to be the overarching category. Construct validity is the approximate truth of the conclusion that your operationalization accurately reflects its construct.
O3 O4 This design controls for all of the seven threats to validity described in detail so far. An explanation of how this design controls for these threats is below. History--this is controlled in that the Validity research methods history events which may have contributed to the O1 and O2 effects would also produce the O3 and O4 effects.
This is true only if the experiment is run in a specific manner--meaning that you may not test the treatment and control groups at different times and in vastly different settings as these differences may effect the results.
Rather, you must test simultaneously the control and experimental groups. Intrasession history must also be taken into consideration.
For example if the groups truly are run simultaneously, then there must be different experimenters involved, and the differences between the experimenters may contribute to effects. A solution to history in this case is the randomization of experimental occasions--balanced in terms of experimenter, time of day, week and etc.
Maturation and testing--these are controlled in that they are manifested equally in both treatment and control groups.
Instrumentation--this is controlled where conditions control for intrasession history, especially where fixed tests are used. However when observers or interviewers are being used, there exists a potential for problems. If there are insufficient observers to be randomly assigned to experimental conditions, the care must be taken to keep the observers ignorant of the purpose of the experiment.
Regression--this is controlled by the mean differences regardless of the extremety of scores or characteristics, if the treatment and control groups are randomly assigned from the same extreme pool.
If this occurs, both groups will regress similarly, regardless of treatment. Selection--this is controlled by randomization. Mortality--this was said to be controlled in this design, however upon reading the text, it seems it may or may not be controlled for.
Unless the mortality rate is equal in treatment and control groups, it is not possible to indicate with certainty that mortality did not contribute to the experiment results. Even when even mortality actually occurs, there remains a possibility of complex interactions which may make the effects drop-out rates differ between the two groups.
Conditions between the two groups must remain similar--for example, if the treatment group must attend treatment session, then the control group must also attend sessions where either not treatment occurs, or a "placebo" treatment occurs. However even in this there remains possibilities of threats to validity.
For example, even the presence of a "placebo" may contribute to an effect similar to the treatment, the placebo treatment must be somewhat believable and therefore may end up having similar results!
The factors described so far effect internal validity. These factors could produce changes which may be interpreted as the result of the treatment. These are called main effects which have been controlled in this design giving it internal validity. However, in this design, there are threats to external validity also called interaction effects because they involve the treatment and some other variable the interaction of which cause the threat to validity.
It is important to note here that external validity or generalizability always turns out to involve extrapolation into a realm not represented in one's sample. In contrast, internal validity are solvable within the limits of the logic of probability statistics.
This means that we can control for internal validity based on probability statistics within the experiment conducted, however, external validity or generalizability can not logically occur because we can't logically extrapolate to different conditions.
Hume's truism that induction or generalization is never fully justified logically. Interaction of testing and X--because the interaction between taking a pretest and the treatment itself may effect the results of the experimental group, it is desirable to use a design which does not use a pretest.
Interaction of selection and X--although selection is controlled for by randomly assigning subjects into experimental and control groups, there remains a possibility that the effects demonstrated hold true only for that population from which the experimental and control groups were selected.
An example is a researcher trying to select schools to observe, however has been turned down by 9, and accepted by the 10th. The characteristics of the 10th school may be vastly different than the other 9, and therefore not representative of an average school.
Therefore in any report, the researcher should describe the population studied as well as any populations which rejected the invitation. Reactive arrangements--this refers to the artificiality of the experimental setting and the subject's knowledge that he is participating in an experiment.
This situation is unrepresentative of the school setting or any natural setting, and can seriously impact the experiment results.
To remediate this problem, experiments should be incorporated as variants of the regular curricula, tests should be integrated into the normal testing routine, and treatment should be delivered by regular staff with individual students.External Validity. Sarah is a psychologist who teaches and does research at an expensive, private college.
She's interested in studying whether offering specific praise after a task will boost.
Construct validity refers to the degree to which inferences can legitimately be made from the operationalizations in your study to the theoretical constructs on . pdf version of this page The field of mixed methods has only been widely accepted for the last decade, though researchers have long been using multiple methods, just not calling them “mixed.” Mixed methods research takes advantage of using multiple ways to explore a research problem.
The theory of validity, and the many lists of specific threats, provide a useful scheme for assessing the quality of research conclusions. The theory is general in scope and applicability, well-articulated in its philosophical suppositions, and virtually impossible to explain adequately in a few minutes. Different methods vary with regard to these two aspects of validity. Experiments, because they tend to be structured and controlled, are often high on internal validity. However, their strength with regard to structure and control, may result in low external validity. Let's use all of the other validity terms to reflect different ways you can demonstrate different aspects of construct validity. With all that in mind, here's a list of the validity types that are typically mentioned in texts and research papers when talking about the quality of measurement.
Basic Characteristics Design can be based on either or. 1 RESEARCH PARADIGMS: METHODOLOGIES AND COMPATIBLE METHODS Abderrazak Dammak* (“All But Dissertation” (ABD) Doctoral Candidate in TESOL) Abstract. Research validity in surveys relates to the extent at which the survey measures right elements that need to be measured.
Coverage includes how market research must meet tests of research validity and research reliability in order to be relevant and useful for marketing decision making. There's an awful lot of confusion in the methodological literature that stems from the wide variety of labels that are used to describe the validity of measures. Validity is the extent to which a concept, conclusion or measurement is well-founded and likely corresponds accurately to the real world based on probability. The word "valid" is derived from the Latin validus, meaning strong. This should not be confused with notions of certainty nor necessity.
In simple terms, validity refers to how well an instrument as measures what it . There are many ways to get information. The most common research methods are: literature searches, talking with people, focus groups, personal interviews, telephone surveys, mail surveys, email surveys, and internet surveys.