Repeated measures ANOVA

There are a fairly complex set of statistical techniques, which go under the heading of repeated measures ANOVA, that do not summarise the serial measurements for each subject as mentioned above, but leave them separated as they are. These methods then provide p-values relating to a comparison of the set of... 

The position of the regulatory authorities is best illustrated by a recent Marketing Authorisation Application by Eli Lilly (www.emea.europa.eu/ humandocs/PDFs/EPAR/cymbalta/19256704en6.pdf) for their anti-depressant duloxetine. The phase III protocols specified a repeated measures ANOVA as the primary method of analysis and the regulatory submission was based on such analyses. The CPMP, however, asked for an additional simpler analysis based on change from baseline as the outcome measure and using LOCF. 

Analysis of variance (ANOVA) analyses were performed using the general statistical package StatView 5.01 (SAS Institute, Cary, NC, USA). The ANOVAs were calculated as repeated-measures ANOVAs with wells as within factor for phase 1 and with plates as within factor for subsequent phases. Specialized statistics, such as comparison of fits of different calibration curves, were calculated in MATLAB 5.1 (MathWorks, Natick, MA, USA) using custom routines. 

Perform statistical analysis utilizing repeated measures ANOVA (JMP software, Version 5 from SAS Institute, Cary, NC) to evaluate the treatment effects on tumor growth. Compare tumor weight measurements between treatment groups utilizing one-way ANOVA. 

Where an endpoint has been determined on several occasions, a repeated measure ANOVA can be used. 

Repeated measures ANOVA W i/y> / i More than 2 groups, linked data... 

The changes of observed parameters were evaluated using repeated-measures ANOVA with Bonferronis corrected J>ost hoc r-test for multiple comparisons of dependent variables. Pearsons correlation coefficient and test were used for the evaluation of dependence of quantitative variables, -values less than 0.05 were considered significant. All statistic analyses were performed using the software package GraphPad Prism 4.0. 

Vasey, M. W, Thayer, J. F (1987). The continuing problem of felse positives in repeated measures ANOVA in psychojiiysiology A multivariate solution. 

Statistical Analysis. Analyses were performed for intent-to-treat and per protocol samples with SAS, version 8.0 software (Cary, NC). ANOVA models were generated utilizing the PROC MIXED procedure. Repeated-measures ANOVA was employed to assess effects of treatment, time (week), and treatment X time interactions for the percentage of change from baseline in body weight, fat mass, and lAF area. 

Fat Mass. Mean changes in fat mass (%) over time are shown in Figure 3. Fat mass decreased from baseline to wk 12 and 24 in both treatment groups. Repeated-measures ANOVA showed significant treatment (P = 0.037) and time (P < 0.001) effects, but no significant treatment x time interaction. 

Intraabdominal Fat Area. Changes in lAF area (%) over time are shown in Figure 4. Repeated-measures ANOVA indicated no significant effects, although both groups tended to show reductions from baseline (P = 0.064 for time effect). 

Secondary Body Composition Variables. Anthropometric measurements did not differ between the DAG and TAG groups at baseline. Total abdominal fat decreased from baseline to wk 24 in both the DAG and TAG oil groups. Repeated-measures ANOVA indicated a significant effect for time. (P < 0.001), but no significant treatment effect. Subcutaneous fat area decreased in both treatment groups from baseline to wk 24. Repeated-measures ANOVA indicated a significant effect for visit (P < 0.001), but no significant treatment effect. 

Fig. 2. Changes in body weight (%) from baseline to wk 2, 4, 6, 8, 12, 16, 20, and 24 among subjects in the intent-to-treat sample assigned to diacylglycerol (DAG) oil (n = 63) or triacylglycerol (TAG) oil (n = 62) treatment groups. Values are means SEM. P-values represent results of repeated-measures ANOVA. The P-value for treatment x time (week) interaction was 0.123. Body weights at baseline were 98.0 1.6 and 97.6 1.8 kg, for the DAG andTAG groups, respectively.

ANOVAs calculate die same F-values as independent ANOVAs, but also calculate an F-value for the subjects. The null hypotheses for diese statistics are diat there is no relationship between the subjects and die dependent variable. Because repeated measures ANOVAs correct for the effect of the subjects, the < thin value for repeated measures ANOVAs are decreased from Ufi - 1) for independent ANOVAs to (i - 1) x (n - 1), where k is the number of responses from each subject, and n is the total number of subjects. The lost degrees of freedom are now used to describe the subjects o ubjects = - 1. 

Independent measures /-test One-way ANOVA Multi-way ANOVA Repeated measures /-test Repeated measures ANOVA Repeated measures ANOVA One-way ANOVA Multi-way ANOVA One-way ANOVA Multi-way ANOVA ... 

With such stringent criteria, we could only include 16 subjects who had completed the entire session without interruption or without using any medication in our analysis. We analyzed the lengths (independent t-test) and variations (F-test) of the menses, intermenses, and menstrual cycle. A repeated measures ANOVA was used to test for the cumulative effect of the treatment over the entire period of the three consecutive cycles. All tests were two-tailed, and the level of significance was set at P < 0.05. 

In order to assess the effect of variation in alarm cue concentration on the duration of alarm responses, we calculated the average shoaling index and vertical area use score for each group of fish during the pre-stimulus period to determine a baseline level of response. Following exposure to the stimulus we calculated the shoaling index and vertical area scores for each group of fish for 1 minute intervals of the 8 minute poststimulus period. We used repeated measures ANOVA to determine the effects of treatment on the response of the fish and whether there was a treatment by time interaction. 

Results from repeated measures ANOVA show there was a significant treatment effect and that there was a treatment by time interaction in terms of both shoaling index (F = 154.90, p < 0.001, Figure 3) and area use (F = 233.05,p <0.001, Figure 4). At higher concentrations the responses were longer and stronger than those at lower concentrations. 

Friedman s repeated measures ANOVA. Differences in vaginal marking across estrous cycle days (D2 vs. PE) were analyzed within each odor condition and on combined scores with Wilcoxon tests. Mann-Whitney tests were used to compare the marking scores of LOT and sham females within each odor condition and cycle day as well as on scores collapsed across estrous days and odor conditions. Flank marking scores were only analyzed (Mann-Whitney test) between groups as LOT females almost never marked in any of the conditions. 

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. 

T-tests were conducted to compare the rested and non-rested sleep and subjective alertness data, and to look at diflerences in PVT performance between the two conditions, relative to baseline performance. Repeated measures ANOVA were used to determine the effects of fatigue on RMSSD, compare the effects of fatigue on RMSSD and on heart rate between the rested and non-rested conditions, and determine whether attitudes towards stress or personahty mediated the effects of fatigue on HRV. Correlation analyses were used to investigate the relationship between personality traits and perceived stress. 

Repeated measures ANOVA carried out on the data revealed that differences between the conditions were unlikely to have arisen due to sampling error (Fj = 8.39, p = 0.004). An overall effect size of 0.48 (Partial Eta squared) showed that almost 50 per cent of the variation in error scores can be accounted for by differing fatigue levels. Post-hoc comparisons revealed that mean reaction time was significantly slower before the non-rested simulation than at baseline M =QAA, f = 2.53, p = 0.032). 

Separate repeated measures ANOVAS examined RMSSD during the simulation as compared with baseline RMSSD in two conditions. Time had a significant effect on RMSSD in both the rested (F, = 4.65, p = 0.003) and non-rested (Fj = 6.96,... 

An additional repeated measure ANOVA compared RMSSD between the two conditions. Time had a significant effect on RMSSD (F = 9.69, p <0.000), however, condition did not. A visual inspection of the data stows HRV decreases sharply after the baseline, and decreases further at the time of the critical incident in the rested condition, but increases shghtly at time of critical incident in the non-rested condition (see Figure 27.2). Post-hoc analyses revealed that RMSSD was significantly different at baseline, as compared to RMSSD at every other point during the simulation. 

Regarding personality traits, a correlation matrix revealed a strong, positive correlation between extraversion and perceived stress in the rested condition (r = 0.695, p <0.05), but no correlation in the non-rested condition. A separate repeated measures ANOVA showed no significant effect of higher neuroticism or higher extraversion on registrars perceived stress between the rested and non-rested conditions (Fj = 1.18, p = 0.31). 

Three or more samples Univariate ANOVA Repeated measures ANOVA... 

A repeated measured ANOVA were used to examine the relationships between muscle activation, COM parameters, COP parameters and COM-COP inclination angles of three ball sizes and two ground contact areas. Post hoc test were used LSD to evaluated. Two-sided significance was defined as p < 0.05. 

The first experiment assessed whether diet manipulations affect the repellency of a predator urine to several prey species. Four rodents served as subjects mountain beaver, house mice, deer mice and guinea pigs. Urine was collected from coyotes maintained on cantaloupe (CU) for 2 weeks and then from the same coyotes fed minced raw meat (MU) for two weeks. Test procedures were similar for all species, though food and deprivation schedules varied. On each of 2 pretreatment days, animals were given their respective foods in cups containing perforated containers with a piece of absorbent paper treated with 1 ml of tap water. On the 2 treatment days that followed, the animals were given the same foods, but the absorbent paper was treated with 1 ml of either CU or MU. Urine samples (1 ml) were pipetted onto pieces of absorbent paper placed inside small (38 mm diameter x 8 mm) perforated plastic containers. For all individuals of each species, the left-right position of CU urine samples was randomly determined on day 1, and then reversed on day 2. The data for each species was evaluated separately in a two-factor repeated measures ANOVA. In each case, urine type was the main effect, with the animals nested within urine type and the repeated measure was days. 

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