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Factorial analysis is a descriptive but very informative approach yielding a simultaneous plot of both groups of variables tested (here emotional reactions and horses characterised by their type of work) and a visualisation of their relationship.
Factorial analysis is a descriptive but very informative approach yielding a simultaneous plot of both groups of variables tested (here time spent performing stereotypies and horses characterized by their type of work) and a visualisation of their relationship.
Standard errors remained stable when adjusting for both groups of variables.
We evaluated both groups of variables (physician characteristics and practice characteristics) for their statistical association with the outcome variables.
The predictive probabilities of all three models are (c-statistics (95% CI)) 0.85 (0.82 to 0.88); 0.80 (0.78 to 0.82) and 0.85 (0.83 to 0.88), respectively, for models 1, 2 and 3. Model 3 combines both groups of variables, has the least number of variables and also the best fit, making it the best among the three for use in practice.
In fact, according to Cohen's formulas [ 44], a sample of 160 is sufficient to detect the effect of two groups of variables on the dependant variable: the first group will formed by three TPB variables (R2 equal to 0.10); the second group will be composed of five additional variables with an increase to R2 equal to 0.02 (alpha = 0.05 and a power of 0.80 for both groups of variables).
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In our study, there were no statistically significant differences between both groups of patients in variables such as age, gender, weight, mechanism of transmission, concomitant pathologies and type of ART, what otherwise could have explained the higher rate of AEs in the exposed group.
Leukemic cells from both groups of mice expressed variable levels of CD4, CD8, CD24, and CD25 cell surface markers, characteristic of bona fide TEL-JAK2 T-cell leukemia (data not shown).
Using both groups of adequacy of care, variables related to structure, process, management, and delays were correlated as independent variables.
The assets of MFA appear when integrating both numerical and categorical groups of variables, and when supplementary groups of data need to be added in the analysis.
However, at time 2 in both groups of school absentees life event variables were significantly increased both in terms of frequency and negative impact.
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