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"A threat to external validity is an explanation of how you might be wrong in making a generalization from the findings of a particular study." [5] In most cases, generalizability is limited when the effect of one factor (i.e. the independent variable) depends on other factors.
A major factor in this is whether the study sample (e.g. the research participants) are representative of the general population along relevant dimensions. Other factors jeopardizing external validity are: Reactive or interaction effect of testing, a pretest might increase the scores on a posttest
Over time, as the novelty wears off, the stress response decreases. This is a threat to external validity when individuals participating in a research study (a novel situation) perceive and respond differently than they would in the normal real world. [2]
A distinction of sampling bias (albeit not a universally accepted one) is that it undermines the external validity of a test (the ability of its results to be generalized to the rest of the population), while selection bias mainly addresses internal validity for differences or similarities found in the sample at hand. In this sense, errors ...
Ecological validity, the ability to generalize study findings to the real world, is a subcategory of external validity. [ 6 ] Another example highlighting the differences between these terms is from an experiment that studied pointing [ 7 ] —a trait originally attributed uniquely to humans—in captive chimpanzees.
Response biases can have a large impact on the validity of questionnaires or surveys. [1] [2] Response bias can be induced or caused by numerous factors, all relating to the idea that human subjects do not respond passively to stimuli, but rather actively integrate multiple sources of information to generate a response in a given situation. [3]
However, confounding may decrease internal validity of a study, and ethical issues may arise in studies involving high-risk. [2] For a great example of a field experiment study, see this study by Milgram, Liberty, Toledo, and Wackenhut exploring the relation between the unique spatial configuration of the queue and the means by which its ...
Internal validity is the approximate truth about inferences regarding cause-effect or causal relationships. 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.