Sentence examples for using other statistical approaches from inspiring English sources

Future studies using other statistical approaches are still needed to understand the role of each item in its respective set, however, SIQ BR is a valid and reliable instrument to evaluate frequency of imagery use among Brazilian-Portuguese speaking athletes.

Once C&RT has been used to identify potentially harmful joint effects, further refinement of these effects, including investigating a dose response relationship or finding specific cut-point values, can be conducted using other statistical approaches.

Nonetheless, this link was demonstrated when using other statistical approaches, including contrasting of weight gains between responders and patients who did not respond, by identifying the degree of improvement associated with every 1-kg gained at 6 weeks, and by calculating the conditional probability of therapeutic response given various amounts of weight gain.

Although authors have suggested the use of other statistical approaches to compare screening modalities [ 10, 11], the area under the full ROC curve remains the most commonly used test for paired screening trials in major American journals [ 1- 3].

As such, it was clear that it was not appropriate to use meta-analytic or other statistical approaches to the pooled data, and so we decided to use a simple strategy to give an insight into the distribution of manic symptoms in different age groups based on the rankings obtained for frequency and severity.

Two other statistical approaches commonly used to improve significance estimates are a penalized t-test and a Z-test using intensity-dependent variance estimates.

Where appropriate, chi-square tests and other statistical approaches were used to test differences in risk among populations.

Here, we present an investigation into visitor preference of the physical properties of 3D printed replicas, using semantic differentials, exploratory factor analysis and other statistical approaches.

Unfortunately, most studies included in this review had a lack of data on non-responders, which meant that it was not possible to adjust estimates for non-response using multiple imputation, inverse probability weighting or other statistical approaches to missing data [ 32].

Apart from empirical curves in some instances, ANOVA and univariate hypothesis testing only the GMO effect, none of the other statistical approaches is currently used nor requested by the authorities.

Other statistical approaches could be used to further investigate the impact of interval censoring (3), but we felt this was outside the scope of the article.