Repeated-measures design

Repeated-measures design. In the context of clinical trials, a trial in which patients are measured repeatedly as a means of determining the efficacy of treatment. Usually the term refers to repeated measurement at different time points of the same outcome variable. Almost all clinical trials in which survival is not the outcome fall into this category. The analysis of such measures can be a delicate matter. The term is also used by psychologists for cross-over design, although this use is potentially confusing and best avoided. 

Summary measures approach. A means of analysing repeated-measures designs which proceeds in two stages. In the first, the repeated measures on each subject are reduced to a summary statistic. In the second stage, these statistics are treated as the data of the problem and analysed conventionally. The advantage is that whereas the original data will not all be independent, the summary measures are. The issue of correlation between the repeated measures is thus finessed. The problem resurfaces to some extent, however, if more than one summary measure is required per subject to capture the essence of the effect of treatment. The main disadvantage of the approach is that it can be inefficient if there are unequal amounts of information per subject. 

Statistics. Data for Expt. 1 were analyzed by one-way analysis of variance (26). Differences among means were checked by least significant difference. In Expt. 2 the repeated measurement design (i.e. three balance periods) was subjected to a split-plot analysis of variance as outlined by Gill and Hafs (27). Differences among pooled means were verified by least significant difference. 

Nesselroade, J. R., Jones, C. J. (1991). Multi-modal selection effects in the study of adult development A perspective on multivariate, replicated, single-subject, repeated measures designs. Experimental Aging Research, 17, 21-27. 

In factorial repeated measures design, the effect of time (or the repeated experimental condition) can be investigated by including it as a factor in the two-way repeated measures ANOVA. It is important to know that the ANOVA does not consider the order of the time points, only the difference between them, and if we want to evaluate a trend or relationship, it is better to use a regression approach. 

Rapid habituation reduces response rates in subsequent trials. Therefore, randomization or counterbalancing of the sequence in which odor treatments are presented is mandatory for experiments with repeated measures designs. To minimize effects of habituation, an intertrial interval of at least one day was established in all but one experiment. 

Another experiment was designed to examine the possible stimulation of courtship by urodaeal substances. In a repeated measures design, males were presented either a post-reproductive female or post-reproductive female painted with an aqueous suspension containing macerated urodaeal glands. Males courted females treated with urodaeal glandular... 

The coefficients a,- are estimated from the results of experiments carried out according to a design matrix such as Table 5.9 which shows a 23 plan matrix. The significance of the several factors are tested by comparing the coefficients with the experimental error, to be exact, by testing whether the confidence intervals Aai include 0 or not. The experimental error can be estimated by repeated measurements of each experiment or - as it is done frequently in a more effective way - by replications at the centre of the plan (so-called zero replications ), see Fig. 5.2. 

Because of vibrations, power stability, and particularly corrosion, commercial laboratory robotic systems available today would have problems on ships. This problem provides an opportunity for research engineers to develop means to modify some sections of the ship to improve power and platform stability. Environmental constraints of a sea-based system were never factored into the design of today s laboratory robots, but the systems could be modified somewhat to reduce these problems. For now, robots would be most feasible for land-based measurements. In the future, however, robots could be important for at-sea measurements, because continuous or repeated measurements are often made over the course of many days. 

Figure 5. An extracted fraction of a sample of sand spiked with two mixtures EPA surrogate spike and phenol spike mixtures. Retention times designate individual components selected to evaluate the repeatability measure of the recovery data.

The basic assumption of this kind of design of experiments without repeating measurements is that each measured result may be described by this model. 

Experiments may be done by design of completely randomized blocks and by repeating measurements in which case analysis of variance has a different form (Table 2.46) ... 

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