Sentence examples for propensity of variable from inspiring English sources

The propensity of variable genetic background to modify phenotypic expression based on a given genetic variant at a given locus (epistasis) is closely related to the genetic diversity of the study population[18].

Previous studies have indicated that the teratoma-forming propensity of iPSCs is variable; however, the relationship between tumorigenic potential and genomic instability in human iPSCs (HiPSCs) remains to be fully elucidated.

Based on these findings, through a combination of biophysical, biochemical and cell biological approaches, we have studied both in vitro and in vivo the actual CC propensity of polyA stretches of variable length, their oligomeric states and their role in intracellular protein aggregation and toxicity.

S e l e c t i o n m o d e l : A w a r e * = X β 2 + ε 2 A w a r e = { 1 i f A w a r e * ≥ 0 0 i f A w a r e * < 0 where Aware* is a latent variable measuring the propensity of being aware of the HPV vaccine and Aware is a dichotomous variable indicating whether or not a respondent is aware of the HPV vaccine.

M a i n p r o b i t m o d e l : D i s c u s s * = X β 1 + ε 1 D i s c u s s = { 1 i f D i s c u s s * ≥ 0 0 i f D i s c u s s * < 0 where Discuss* is a latent variable measuring the propensity of a vaccine discussion occurring between a respondent and her HCP and Discuss is a dichotomous variable indicating whether or not an HPV vaccine discussion has occurred between a respondent and her HCP.

Due to the number of variables, propensity scores (PS) were estimated for each patient using a logistic regression model.

26 Secondly, several features aided in establishing a balanced comparison group, including the requirement for diagnoses of mental disorder with high propensity for treatment with stimulants and the broad selection of variables for propensity score adjustment.

We used linear regression analysis to explore the association between these micro political variables and the propensity of appetitive violence.

As the household is the unit of enrolment in Nouna's CBHI scheme and previous studies have shown the household head as a prominent voice in the decision to enrol (de Allegri et al. 2006b), the logit model for the propensity of enrolling in CBHI used explanatory variables at the household level wherever possible.

Furthermore, access to information and general environmental concern were found to be important variables to explain the propensity of farmers to participate.

He says his company's current models use nearly 500 individual variables to predict the propensity of an individual consumer to default.