REPEATED MEASURES DESIGN 3
Repeatedmeasures design in a research is the use of a subject for multiplemeasurements. The subjects have exposure to all kinds ofmeasurements, which makes them better at the form of representation.The models also helps in the establishment of a better platform forviewing the reactions of the typical subjects to the variousvariables (Lawal, 2014).
Repeatedmeasures design aids in the research of a subject for an extendedperiod. The items are well looked into and their reactions over timefor consideration. The method also has a higher statistical power andthe potential of the research studies has a greater finesse ascompared to the other designs of research (Vittingoff et al. 2011).Repeated measures design provides the capability to conduct a studyon a subject over an extended period, and also provides the abilityto use fewer subjects for the specific studies. Therefore, the designis efficient in handling long-term projects and surveys.
Nonetheless,repeated measures design also poses some limitations in the event ofa study. The research design exposes the subjects to order effects.When an issue passes under numerous variable studies, the particulartopic is worn out, and functionality reduces (Thomas & Zumbo,2012). The move makes the study to have a diversion in the resultsdue to the high rate of the subjects wearing out. Therefore, thedesign is non-efficient in qualitative models.
Inconclusion, the repeated designs model is a useful model for thestudy of long-term projects. The design allows for the use ofparticular subjects over an extended period and also tests the topicswith numerous variables. However, this also affects the workabilityof the schedule as the subjects suffer from order effects. Therefore,the research design stands as a disadvantage to the quality of thestudies.
Lawal,B. (2014). Repeated measures design. In AppliedStatistical Methods in Agriculture, Health and Life Sciences(pp. 697-718). Springer International Publishing.
Thomas,D. R., & Zumbo, B. D. (2012). Difference scores from the point ofview of reliability and repeated-measures ANOVA in defense ofdifference scores for data analysis. Educationaland Psychological Measurement,72(1),37-43.
Vittinghoff,E., Glidden, D. V., Shiboski, S. C., & McCulloch, C. E. (2011).Regressionmethods in biostatistics: linear, logistic, survival, and repeatedmeasures models.Springer Science & Business Media.