Error In Casual Validity
which a study minimizes systematic error (or 'bias'). It contrasts with external validity, the degree to which it is warranted to generalize results to other contexts. Contents 1 Details 2 Factors affecting internal validity 3 Threats to internal validity 3.1 Ambiguous temporal precedence 3.2 Confounding 3.3 Selection bias 3.4 History 3.5 Maturation 3.6 Repeated testing (also referred to as testing effects) 3.7 Instrument change (instrumentality) 3.8 Regression toward the mean 3.9 Mortality/differential attrition 3.10 Selection-maturation interaction 3.11 Diffusion 3.12 Compensatory rivalry/resentful demoralization 3.13 Experimenter bias 4 See also 5 References 6 External links Details[edit] Inferences are said to possess internal validity if a causal relation between two variables is properly demonstrated.[1][2] A causal inference may be based on a relation when three criteria are satisfied: the "cause" precedes the "effect" in time (temporal precedence), the "cause" and the "effect" are related (covariation), and there are no plausible alternative explanations for the observed covariation (nonspuriousness).[2] In scientific experimental settings, researchers often manipulate a variable (the independent variable) to see what effect it has on a second variable (the dependent variable).[3] For example, a researcher might, for different experimental groups, manipulate the dosage of a particular drug between groups to see what effect it has on health. In this example, the researcher wants to make a causal inference, namely, that different doses of the drug may be held responsible for observed changes or differences. When the researcher may confidently attribute the observed changes or differences in the dependent variable to the independent variable, and when the researcher can rule out other explanations (or rival hypotheses), then the causal inference is said to be internally valid.[4] In many cases, however, the ma
try to establish a causal relationship. It's not relevant in most observational or descriptive studies, for instance. But for studies that assess the effects of social programs or interventions, internal validity is perhaps the primary consideration. In those contexts, you would like to be able to conclude that your program or treatment made a difference -- it improved test scores or reduced symptomology. But there may be lots of reasons, other than your program, why test scores may improve or symptoms may reduce. The key question in internal validity is whether observed changes can https://en.wikipedia.org/wiki/Internal_validity be attributed to your program or intervention (i.e., the cause) and not to other possible causes (sometimes described as "alternative explanations" for the outcome). One of the things that's most difficult to grasp about internal validity is that it is only relevant to the specific study in question. That is, you can think of internal validity as a "zero generalizability" concern. All that http://www.socialresearchmethods.net/kb/intval.php internal validity means is that you have evidence that what you did in the study (i.e., the program) caused what you observed (i.e., the outcome) to happen. It doesn't tell you whether what you did for the program was what you wanted to do or whether what you observed was what you wanted to observe -- those are construct validity concerns. It is possible to have internal validity in a study and not have construct validity. For instance, imagine a study where you are looking at the effects of a new computerized tutoring program on math performance in first grade students. Imagine that the tutoring is unique in that it has a heavy computer game component and you think that's what will really work to improve math performance. Finally, imagine that you were wrong (hard, isn't it?) -- it turns out that math performance did improve, and that it was because of something you did, but that it had nothing to do with the computer program. What caused the improvement was the individual attention that the adult tutor gave to the child -- the
with insertion of our examples. Problem and Background Experimental method and essay-writing Campbell and Stanley point out that adherence to experimentation dominated the field of education through the 1920s (Thorndike http://web.pdx.edu/~stipakb/download/PA555/ResearchDesign.html era) but that this gave way to great pessimism and rejection by the late 1930s. However, it should be noted that a departure from experimentation to essay writing (Thorndike to Gestalt Psychology) occurred most http://www.medscape.com/viewarticle/414875_3 often by people already adept at the experimental tradition. Therefore we must be aware of the past so that we avoid total rejection of any method, and instead take a serious look at error in the effectiveness and applicability of current and past methods without making false assumptions. ReplicationMultiple experimentation is more typical of science than a once and for all definitive experiment! Experiments really need replication and cross-validation at various times and conditions before the results can be theoretically interpreted with confidence. Cumulative wisdomAn interesting point made is that experiments which produce opposing theories against each other probably will not have clear error in casual cut outcomes--that in fact both researchers have observed something valid which represents the truth. Adopting experimentation in education should not imply advocating a position incompatible with traditional wisdom, rather experimentation may be seen as a process of refining this wisdom. Therefore these areas, cumulative wisdom and science, need not be opposing forces. Factors Jeopardizing Internal and External Validity Please note that validity discussed here is in the context of experimental design, not in the context of measurement. Internal validity refers specifically to whether an experimental treatment/condition makes a difference or not, and whether there is sufficient evidence to support the claim. External validity refers to the generalizibility of the treatment/condition outcomes. Factors which jeopardize internal validity History--the specific events which occur between the first and second measurement. Maturation--the processes within subjects which act as a function of the passage of time. i.e. if the project lasts a few years, most participants may improve their performance regardless of treatment. Testing--the effects of taking a test on the outcomes of taking a second test. Instrumentation--the changes in the instrument, observers, or scorers which may produce changes in outcomes. Statistical regression--It is also known as regression to the mean. This threat is caused by th
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