Validity and reliability in quantitative studies

Statistical regression: The natural effect of participants at extreme ends of a measure falling in a certain direction just due to the passage of time rather than the effect of an intervention.If a study takes place over a period of time in which it is possible that participants naturally changed in some way (grew older, became tired), then it may be impossible to rule out whether effects seen in the study were simply due to the effect of time. Maturation: This describes the impact of time as a variable in a study.Instrumentation: It's possible to 'prime' participants in a study in certain ways with the measures that you use, which causes them to react in a way that is different than they would have otherwise.Historical events: May influence the outcome of studies that occur over a period of time, such as a change in the political leader or natural disaster that influences how study participants feel and act.Experimenter bias: An experimenter behaving in a different way with different groups in a study, which leads to an impact on the results of this study (and is eliminated through blinding).This can also lead to another issue called resentful demoralization, in which a control group tries less hard because they feel resentful over the group that they are in. Diffusion: This refers to the treatment in a study spreading from the treatment group to the control group through the groups interacting and talking with or observing one another.Confounding: A situation in which changes in an outcome variable can be thought to have resulted from some third variable that is related to the treatment that you administered.Attrition: Participants dropping out or leaving a study, which means that the results are based on a biased sample of only the people who did not choose to leave (and possibly who all have something in common, such as higher motivation).Study protocol: Following specific procedures for the administration of treatment so as not to introduce any effects of, for example, doing things differently with one group of people versus another group of people.Randomization: Randomly assigning participants to treatment and control groups, and ensures that there is not any systematic bias between groups.Random selection: Choosing your participants at random or in a manner in which they are representative of the population that you wish to study.Experimental manipulation: Manipulating an independent variable in a study (for instance, giving smokers a cessation program) instead of just observing an association without conducting any intervention (examining the relationship between exercise and smoking behavior).Blinding: Participants-and sometimes researchers-who are unaware of what intervention they are receiving (such as by using a placebo in a medication study) to avoid this knowledge biasing their perceptions and behaviors and thus the outcome of the study.

Validity and reliability in quantitative studies