Sentence examples for visits as a function from inspiring English sources

We further explored the relationship between HAART and liver function by examining the lnAPRI at each clinic visits as a function of the dose of HAART received up to that time.

We found no differences in inpatient visits as a function of turning 65.

Bivariate and multivariable poisson regression analysis was used to assess the number of maternal health care visits as a function of social network characteristics, education, ethnicity, age, and urban and rural residence.

We used generalized additive models assuming Poisson distribution, to analyze the daily emergency hospital visits as a function of the pollutant levels, and adjusted for meteorological variables, day of week, and time trend with splines.

We applied a time series analysis approach to determine whether excess deaths and ED visits occurred during the 2011 heat wave by modeling daily counts of deaths and ED visits as a function of the 2011 heat wave using different heat-wave definitions.

Drawing on the theory of job search from microeconomics, we estimate the expected number of patches visited as a function of just two variables: the coefficient of variation of the rate of energy gain among patches, and the ratio of the expected time exploiting a randomly chosen patch and the expected time travelling between patches.

The first logistic regression model calculated the probability of participating in the subsequent visit as a function of air pollution concentration measured at the previous visit.

The GEE approach was used to fit a logistic regression model for pubertal onset at each visit as a function of age at visit, with adjustment for potential confounders and correlation among multiple visits via an autoregressive structure.

Multivariate logistic regression was conducted using Generalized estimating Equations (GEE) to estimate the odds of recommending a hospital admission or ER visit as a function of infant age, temperature, whether the infant recently received a vaccine, and whether the fever was reported during or after office hours, adjusting for practice type and socio-demographic variables.

For each domain and summary score of each instrument, a statistically significant interaction effect for sustainer status by visit was observed, indicating that changes in each score across visit differed as a function of sustainer status.

It can be used to predict quantitatively how long an individual should stay on different patches that are visited sequentially, as a function of the average time needed to move from one patch to another, and on the dynamics of gain acquisition in patches.