Future studies could evaluate the underlying factors contributing to higher healthcare utilization rates as well as the factors underlying more favorable outcomes such as lower utilization rates (for example, regression analyses with ER visits and inpatient hospitalizations as outcome variables).
Because of the possibility of de-anonymising single cases, data are only accessible in not-too-sparse strata, obviating all analyses that use individual case data, for example, regression analyses with simultaneous adjustments for more than one confounder, or even interactions between confounders.
For example, use regression analyses of performance and 360-degree feedback data to determine training priorities.
For example, our regression analyses clarified interactions between the maternal parent and % crop alleles in late fall by showing that while germination increased with % crop alleles, maternal types differed in their maladaptive germination responses (i.e. their slopes in Fig. 3).
For example, in regression analyses, women who were White, higher educated, English native speakers and of higher income were less likely to over-report cervical cancer screening in Ontario than their respective counterparts, but this did not hold true for the other screening types.
For example, the multivariable regression analyses suggest that reducing the overall frequency of on-to-farm visits would be more effective for FD transmission, in contrast to limiting the clustering of consecutive visit days for DD transmission (Tables 3a and 3b).
For example, in the logistic regression analyses, the results for PCE and vinyl chloride were based on two cases with high exposure and the result for DCE was based on three cases with high exposure.
Risk prediction models are statistical algorithms, which may be simple genetic risk scores (for example, risk allele counts), may be based on regression analyses (for example, weighted risk scores or predicted risks), or may be based on more complex analytical approaches such as support vector machine learning or classification trees.
For example, the results from the regression analyses with the matched samples (with covariates as controls) suggest a significant treatment effect for Singapore and Sweden.
In multiple regression analyses for example, microvascular complications, heart failure and depression were most strongly related to decreased HRQoL, independently of the duration of diabetes while patients without symptomatic co-morbidities did not have a significantly reduced HRQoL [ 10].
