The advantages and disadvantages of repeated measures
A repeated-measures design is using the same participants for all of your experimental conditions (Field, 2011). This is in contrast to an independent groups design, in which you have different groups of participants for the different experimental conditions so that each participant is exposed to just one condition (Howitt & Cramer, 2011).
A benefit of using repeated-measures (using the same participants for both manipulations) is it allows the researcher to exclude the effects of individual differences that could occur if two different people were used instead (Howitt & Cramer, 2011). Factors such as IQ, ability, age and other important variables remain the same in repeated-measures as it is the same person taking part in each condition (Field, 2011). This is one of the disadvantages of using independent groups.
Another benefit of repeated-measures is it requires fewer participants than independent groups. For example, whereas repeated-measures may only need 20 participants, independent groups would need 20 participants for each condition (Howitt & Cramer, 2011). Repeated-measures are therefore quicker and easier to successfully recruit the necessary number of participants.
Although these strengths favour repeated-measures, independent groups do have strengths where repeated-measures weaken. For example, using the same participants for all conditions leads to difficulties counteracting problems of order effects (performance changing due to the order of exposure to conditions). Results could therefore be due to boredom effecting concentration and performance in reaction times or accuracy (Pan, Shell & Schleifer, 1994; Bergh & Vrana, 1998). Effects could also be due to repetition causing participants’ results to improve because they were given more chance to practice and become familiar with the task (Collie, Maruff, Darby & McStephen, 2003).
Order effects can be reduced by counterbalancing (Field, 2011). For example, half the participants would be exposed to control A first and then control B, and the other half of participants exposed to control B and then control A (Howitt & Cramer, 2011). The results should then be less affected by factors such as boredom and practice. Additionally, researchers can also provide breaks during the experiment to counteract boredom and loss of concentration (Pan, Shell & Schleifer, 1994).
Another weakness of repeated-measures is the need for additional experimental materials. For example, if a study was testing how Factor A and Factor B affected participants’ memory for learning lists, in repeated-measures the researcher would require a different list of words for participants to memorise for both Factor A and B, whereas in independent groups the same list could be used for each factor because each group only sees the material once (Nilsson, Soli & Sullivan, 1994). Therefore, in using repeated-measures the individual differences of participants are reduced but this instead produces problems with individual differences between the materials participants are exposed to. Therefore results may be due to these differences in materials rather than the independent variable in question. The materials must therefore be carefully examined to ensure equal quality in factors such as difficulty (Riedel, Klaassen, Deutz, Someren & Praag, 1999).
Therefore there are advantages and disadvantages for both repeated-measures and independent groups. Whereas repeated-measures are good for quick recruitment, less participants and removing individual differences between participants, independent groups are good for avoiding order effects and differences in experimental materials. Each study must have careful consideration into which design would best meet the needs of the study. Once chosen, the problems related to the design (which both have) must be reduced to have as little effect on results as possible.
Bergh, O. V., & Vrana, S. R. (1998). Repetition and boredom in a perceptual fluency/ attributional model of affective judgements. Cognition and Emotions, 12, 533-553. doi: 10.1080/026999398379556
Collie, A., Maruff, P., Darby, D. G., & McStephen, M. (2003). The effects of practice on the cognitive test performance of neurologically normal individuals assessed at brief test-retest intervals. Journal of the International Neuropsychological Society, 9, 419-428. doi: 10.1017/S1355617703930074
Field, A. (2011). Discovering Statistics Using SPSS. (3rd ed.). (pp. 15-18).Thousand Oaks,California: SAGE Publications
Howitt, D., & Cramer, D. (2011). Introduction to Research Methods in Psychology. (3rd ed.). (pp. 164, 179-181). Harlow, Essex: Pearson Education Limited
Nilsson, M., Soli, S. D., & Sullivan, J. A. (1994). Development of hearing in noise test for the measurement of speech reception thresholds in quiet and in noise. Journal of the Acoustical Society of America, 95, 1085-1099. [Abstract] Retrieved from http://asadl.org/jasa/resource/1/jasman/v95/i2/p1085_s1?isAuthorized=no
Pan, C. S., Shell, R. L., & Schleifer, L. M. (1994). Performance variability as an indicator of fatigue and boredom effects in a VDT data-entry task. International Journal of Human-Computer Interaction, 6, 37-45. doi: 10.1080/10447319409526082
Riedel, W. J., Klaassen, T., Deutz, N. E. P., Someren, A., & Praag, H. M. (1999). Tryptophan depletion in normal volunteers produces selective impairment in memory consolidation. Psychopharmacology, 141, 362-369. doi: 10.1007/s002130050845