Sentence examples for mean age percent from inspiring English sources

We, therefore, conducted a meta-regression [ 24] analysis including sample size, mean age, percent men, and duration of the follow-up.

We explored potential heterogeneity in estimates of the treatment effects with univariate meta-regression (for sample size, mean age, percent men, and duration of the follow-up period) [ 24].

The approach to adjustment followed that of the complete patient-level data analysis and included the following group-level covariates: mean age, percent female, an indicator of whether or not the percent WHO stage 3/4 was ≤/> 90%, and region.

coded studies across 10 characteristics of the sample (year of publication, mean age, percent female, percent ethnic minority, mean duration of type 1 diabetes, sample size [total, experimental, and control], mean A1C at baseline and follow-up [experimental and control], delivery format of the intervention [group versus individual], time to follow-up, and statistics reported for adherence and A1C).

The following HRR level variables for the geographic regions were based on 2000 census data (the most currently available data at the time of our analysis): mean age; percent African American; and a composite measure of socioeconomic status that was validated for a similar population and based on income, housing value, monthly rent, education level, and employment (13).

Extracted data included features of the study design (i.e., crossover or parallel design and presence of a washout period), intervention periods, characteristics of patients (mean age, BMI, percent men, and percent those using hypoglycemia agents).

The mean age and percent distribution of the satisfaction level of the clients were calculated.

There were no significant differences in the mean age, weight, percent body fat, hemoglobin (Hb), fasting blood glucose, post prandial blood glucose and lipid profile between the experimental and placebo groups (Table 1).

We specified the number of males in each cohort as the dependent variable and included, as covariates, the number of females as well as three characteristics of the cohorts (i.e., mean maternal age, percent non-Hispanic white, and percent African American) that prior literature suggests could confound the association between the economy and the sex ratio.

We used 2010 Census data to create an adjusted model, which considered median age, percent of females in the population, percent college educated and the mean persons per household for each county.

Mean age, BMI, and percent male were 54.3 years, 26.5, and 64.5% in group A and 59.9, 27.0, and 53.1% in group B, respectively (Table 2).