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The advantages and disadvantages of repeated measures

December 1, 2011

Repeated measures are the method of using the same participants in different experimental manipulations (Field, 2011). This is in contrast to independent groups in which different groups of participants are exposed to just one experimental condition (Howitt & Cramer, 2011). Repeated measures, in using the same participants for both manipulations, allow the researcher to exclude the effects of individual differences that could occur in independent groups (Howitt & Cramer, 2011). Factors such as IQ, ability, age and other important variables remain the same (Field, 2011). This is a strength of repeated measures and one of the greater disadvantages of independent group methods. As the same participants are used, it requires fewer participants than the independent group as independent need an equal minimum number of different participants for each situation (Howitt & Cramer, 2011). This makes successfully recruiting the necessary number of participants quicker and easier in repeated measures.

Although these strengths favour repeated over independent groups, independent has strengths where repeated measures weaken. The use of the same participants leads to difficulties counteracting problems of order effects and the need for additional materials. An effect observed in results could therefore be due to boredom affecting concentration and performance such as reaction time, and accuracy caused by repetition (Pan, Shell & Schleifer, 1994; Bergh & Vrana, 1998). Effects could also be due to practice causing participants’ results to improve because they were given more chance to practice and become familiar with the task (Collie, Maruff, Darby & McStephen, 2003). The order effects of an experiment can be reduced by counterbalancing (Field, 2011). This involves randomly assigning the order of the experimental manipulations participants are exposed to. 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 collected should then be less affected by factors such as boredom and practice. Researchers can also provide opportunities to take a break during the experiment to counteract boredom and loss of concentration (Pan, Shell & Schleifer, 1994).

If a study was testing how Factor A and Factor B affected memory the researcher would require a different list of words for participants to memorise for 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). In using repeated measures the individual differences of participants is reduced but this instead produces problems with individual differences between the materials or environments the participants are exposed to. Therefore the result may be due to these differences in materials rather than the independent variable in question. The materials must be carefully examined to ensure equal quality in factors such as difficulty (Riedel, Klaassen, Deutz, Someren & Praag, 1999).

The advantages and disadvantages of repeated measures must be compared with the benefits of using independent groups. Each study must have careful consideration into which design would best meet the needs of the study. Problems related to the design must be reduced to have as little effect on results as is possible. Both methods are not without difficulty and the researcher must decide which would best produce results the investigation is studying.

References

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

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3 Comments
  1. Agreeing with dsowen, the type of design used should be dependent upon the specific research question. Sackett & Wennberg (1997), suggest that the research design is entirely dependent on the question asked and as a result, it could be assumed neither could be seen as a better option for research. Both independent and dependent designs have their weaknesses. Repeated measures can lead to positive bias (Vasey & Thayer, 1987) because results may not be valid due to demand characteristics and order effects/boredom as described by dsowen. Also, any incorrect use of supposition related to variance or covariance can mean too many null hypotheses are rejected (McCall & Appelbaum, 1973). Finally, participants often drop out prematurely from longitudinal studies (Little, 1995) and this can lead to unbalanced results in repeated measure designs.

    References:

    Little, R. J. A. (1995). Modelling the Drop-Out Mechanism in Repeated-Measures Studies. Journal of the American Statistical Association, 90, 1112-1121.

    McCall, R. B. & Appelbaum, M. I. (1973) Bias in the Analysis of Repeated-Measures Designs: Some Alternative Approaches. Child Development, 44, 401-415. Retrieved from: http://www.jstor.org/stable/1127993

    Sackett, D. L. & Wennberg, J. E. (1997) Choosing the Best Research Design for Each Question: It’s time to stop squabbling over the “best” methods. BMJ, 315, 1636. doi: 10.1136/bmj.315.7123.1636

    Vasey, M. W. & Thayer, J. F. (1987) The Continuing Problem of False Positives in Repeated Measures ANOVA in Psychophysiology: A Multivariate Solution. Psychophysiology, 24, 479-486. DOI: 10.1111/j.1469-8986.1987.tb00324.x

  2. psuf09 permalink

    Another advantage for repeated measures is that the results can be directly compared, which can be problematic for independent measures. However, it can suffer from demand characteristics, as the participants may realise what the experiment is about once they begin the second and see how it differs from the first. If a participant knows what the experiment is about they may behave how they think they expected to, rather than how they would normally.

    Another design which combines the advantages of both independent and repeated measures is matched pairs design; matching every participant in one group with a very similar person in the other group. This allows the groups to be directly comparable and eliminates order and practice effects, whilst still controlling individual differences.

    References:

    Howitt, D., & Cramer, D. (2008). The basic laboratory experiment. Introduction to Research Methods in Psychology (2nd ed.) (pp. 159-183). Harlow, Essex: Pearson Education Limited.

  3. There are ways of dealing with the weaknesses of repeated measures. The biggest weakness of the repeated measures design is the order of conditions and how this may affect participant performance. A way of dealing with this is counterbalancing. This ensures that each condition is tested first and second in equal amounts. This usually involves the sample being split into two groups, one group does condition A first and then condition B whilst the second group would do condition B first then condition A.
    Another weakness of the repeated measures design is that one condition may be harder than the other condition. To overcome this, experimenters must ensure that tests are equivalent. For example if participants were given to list of words to learn, to see whether memory recall was better in the afternoon or in the morning, a list of words would be created, all words being of similar length etc. these words would then be randomly allocated to two lists ensuring that both lists were equivalent.

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