2011
DOI: 10.1016/j.bbr.2011.03.007
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Statistical analysis of latency outcomes in behavioral experiments

Abstract: In experimental designs of animal models, memory is often assessed by the time for a performance measure to occur (latency). Depending on the cognitive test, this may be the time it takes an animal to escape to a hidden platform (water maze), an escape tunnel (Barnes maze) or to enter a dark component (passive avoidance test). Latency outcomes are usually statistically analyzed using ANOVAs. Besides strong distributional assumptions, ANOVA cannot properly deal with animals not showing the performance measure w… Show more

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Cited by 107 publications
(57 citation statements)
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“…Transfer latencies were plotted as cumulative incidence of transfer and compared by Cox regression (Jahn-Eimermacher et al, 2011). For better comparability, we determined the T 50 -values, i.e., the values when 50% of the mice entered the TC.…”
Section: Methodsmentioning
confidence: 99%
“…Transfer latencies were plotted as cumulative incidence of transfer and compared by Cox regression (Jahn-Eimermacher et al, 2011). For better comparability, we determined the T 50 -values, i.e., the values when 50% of the mice entered the TC.…”
Section: Methodsmentioning
confidence: 99%
“…It is often difficult to decide how to analyze behavioral latency data because they often lack a normal distribution with censored values (non-responders); therefore, parametric statistical tests are not an appropriate choice. We chose to use the an approach similar to survival analysis on emesis latency data (Horn et al 2013c), which can be analyzed by Cox regression and does not require assumptions about the nature of sampling distributions (Jahn-Eimermacher et al 2011). A follow-up report showed that this type of analysis could be more sensitive than parametric statistics (i.e., total number of emetic episodes) when comparing groups (Horn et al 2014).…”
Section: Can We Measure Nausea In Non-human Animals?mentioning
confidence: 99%
“…Furthermore, behavioral latency data typically do not have a normal distribution; and, therefore, parametric analyses are not appropriate. The current approach, based on analysis of behavioral latencies in rodents (Jahn-Eimermacher et al, 2011), does not require assumptions about the distribution of data, and values from non-responding animals can also be included (i.e., censored values). Plotting the cumulative incidence of emesis shows the number of responding animals, group medians and quartiles, and illustrates the temporal differences between groups that can be analyzed using Cox regression (Jahn-Eimermacher et al, 2011).…”
Section: Discussionmentioning
confidence: 99%
“…Reported optimal parameters for each emetic stimulus were used, including 1 Hz of reciprocating lateral motion, 5 mg/kg nicotine (sc), and 120 mg/kg CuSO 4 (ig) (Chan et al, 2007; Javid et al, 1999; Rudd et al, 1999). New emetic measures included duration (time from first to last episode), rate, and the variability of the timing of responses (i.e., the standard deviation of the inter-episode interval, SD-I); and, a survival analysis was applied to emetic latency (Jahn-Eimermacher et al, 2011). Behavioral patterns associated with emesis were assessed using statistical temporal pattern (T-pattern) analysis to determine potential sickness or nausea-like behavior (Horn et al, 2011; Magnusson, 2000).…”
Section: Introductionmentioning
confidence: 99%