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Exact(7)
First, the probability of having a positive slide was separately estimated for trophozoites by logistic regression models, including variables for the effect of age, week of sampling and delay between the end of the preceding anti-malarial treatment and the date of sampling for each thick blood film.
Subsequent multiple logistic regression models including variables with p < 0.2 from the univariate analysis were calculated.
In addition, the models including variables from both BC and HDR show a better fit taking complexity into account.
Logistic regression was used for multivariable comparisons with backward deletion from first step models including variables significant at 0.1 level in the univariable analysis.
Following the examination of simple descriptive tables, we will fit longitudinal ordinal regression models including variables representing condition type (neurological, metabolic, or chromosomal), time from diagnosis, age, and sex.
Our study shows that all the four models have a high discrimination capacity but models including variables retrieved from both BC and HDR show a higher discrimination capacity than the ones including only variables from the HDR.
Similar(53)
Multivariate analysis of covariance and logistic regression models including variable most predictive for the dependent variables were built.
The models included variables that were established as confounders [17].
Many models included variables related to spatial relationships of structures.
Finally, the models include variables pertaining to the use of SO2.
Both our matching and DiD models include variables of economic development (e.g., number of convenience and grocery stores, proportion of the population with income below poverty etc).
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