2016
DOI: 10.1038/nprot.2016.048
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Analysis of longitudinal data from animals with missing values using SPSS

Abstract: Testing of therapies for disease or injury often involves the analysis of longitudinal data from animals. Modern analytical methods have advantages over conventional methods (particularly when some data are missing), yet they are not used widely by preclinical researchers. Here we provide an easy-to-use protocol for the analysis of longitudinal data from animals, and we present a click-by-click guide for performing suitable analyses using the statistical package IBM SPSS Statistics software (SPSS). We guide re… Show more

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Cited by 90 publications
(69 citation statements)
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“…15 Random-effects models were constructed with FTS as dependent variable; subject ID as random factor; and group, time, and group by time interaction as fixed factors. To evaluate effects of viral vector injection or DREADD expression on seizure activity, FTS was compared before and 3 weeks after injection with rAAV in four mice (see higher) using a paired t-test.…”
Section: Effect On Spontaneous Hippocampal Seizuresmentioning
confidence: 99%
See 1 more Smart Citation
“…15 Random-effects models were constructed with FTS as dependent variable; subject ID as random factor; and group, time, and group by time interaction as fixed factors. To evaluate effects of viral vector injection or DREADD expression on seizure activity, FTS was compared before and 3 weeks after injection with rAAV in four mice (see higher) using a paired t-test.…”
Section: Effect On Spontaneous Hippocampal Seizuresmentioning
confidence: 99%
“…First, the effects of the highest CNO and clozapine doses were compared between DREADD and non-DREADD animals using the MIXED procedure in IBM SPSS Statistics. 15 Random-effects models were constructed with FTS as dependent variable; subject ID as random factor; and group, time, and group by time interaction as fixed factors.…”
Section: Effect On Spontaneous Hippocampal Seizuresmentioning
confidence: 99%
“…For sessions that didn’t include any data, a non-zero identifier was automatically placed for mean turn angle and success rate. This non-zero identifier is called a NaN, or “Not-a-Number,” and is commonly used to represent missing data (Duricki et al 2016). After keeping or discarding files, the Annotate Now option was chosen from the next prompt (Fig.…”
Section: Resultsmentioning
confidence: 99%
“…However, after injury, a subject may be very impaired and not engage with the task. In these cases, the success rate and turn angle is recorded as a “Not-a-Number” (NaN), or the average of the success rate and turn angle of the trials present in the file (Duricki et al 2016). …”
Section: Methodsmentioning
confidence: 99%
“…An unstructured linear mixed effects model was applied to examine the main effect of repeated stimulation (second neutral and conditioned) and interaction effect with different condition modalities (warm, cool, interlaced warm and cool). The advantage of the LMM is that one can account for missing data when analyzing longitudinal data47. From this model, we were most interested to determine if conditioning differentially impacted CHEPs outcomes (i.e., interaction effect).…”
Section: Methodsmentioning
confidence: 99%