The study design strategy describes the ways in which people fall into distinctive groups and the ways in which the variables are manipulated to respond to one or more evaluation questions. A classic example of a design strategy is when individuals are separated into two groups and one group participates in an experimental program (receives the treatment) while the second participates in a placebo program (does not receive the treatment). Most problems are always due to poor design of the study. A good study design strategy provides a comprehensible description of various groupings of individuals. It also shows how manipulation of variables occurs in attempt to answer different evaluation questions. A clear distinction emerges when the groups comprise people with varying roles and responsibilities. The study design consists of a range of elements that includes measurement accuracy and the unit of recorded measure. Gauging the resulting outcomes of a study design would mainly depend on the baseline. A great variation exists between the experimental studies and non-experimental studies. The researchers may also consider the upstream and downstream causes. The reality that an individual or groups participate in and experimental program do not stop others from participating in programs in which they have exceptional interest. The individuals who participate in such group are subject to specialized treatment as compared to others. The second group comprises individuals whose primary aim is to participate in placebo program where they do not receive any specialized treatment.
External validity is primarily concerned with universal inferences in a study of science. The experiments form the basis of the experimental strength in an external validity array. In essence, the external validity shows the extent to a generalized analysis of a study in relation to other people and institutions. Threats to external validity include aptitude, situation, pre-test effects, post-test effects, Rosenthal effects and reactivity. Internal validity on the other hand reflects the degree of warranting the causal conclusion, always based on a study. The extent to which the study seeks to minimize the systematic error invites the process of constituting such warrant. The threats to internal validity include confounding, selection bias, ambiguous temporal precedence, history, maturation, mortality and regression. Actually, the outcomes of a research study maybe valuable to the extent of their precise as well as confident interpretation. Any core of discussion as regards validity focuses on the issues of confident and precise interpretation. Internal validity is momentous for an array of reasons. First, it facilitates the process of conducting research, which mainly aims at determining cause-and-effect relationships. Secondly, it influences conclusions as to whether the changes in the independent variables cause or trigger observed changes in the dependent variables. Internal validity also helps to decide whether the evidence of such a conclusion is poor or good. In the event that the study shows a high level of internal validity, it is arguably correct to conclude that there exists strong evidence of causality.
In contrast, if the study illustrates an element of low internal validity then it is right to conclude that there is little or no evidence of causality. The variables of internal validity include extraneous variables and confounding variables. Extraneous variables may adequately compete with the independent variable in attempt to explain the outcomes of the study. A confounding variable refers to extraneous variable that influences the dependent variables. Through a comprehensible assessment and analysis of the internal and external validity threats, the research study determines whether the conclusion of the investigation is correct. It is also necessary to determine whether changes in the independent variable are responsible for the observed variations. The variation in the dependent being attributable to other causes is also a matter of concern.
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