Sentence examples for weighting for differences from inspiring English sources

Exact(1)

The approach adopted for the analyses of cognitive aging used all of the available randomized evidence for the effects of B vitamins on cognitive function, after appropriate weighting for differences between trials by duration of treatment and extent of homocysteine reduction.

Similar(59)

Furthermore, we assessed the impact of pharmacy discounts and weighting for seasonal differences in the data collection on the results.

Controlling for living alone, self-rated health and experience of cancer, and weighting for non-representativeness, made little difference to the results.

Controlling for living alone, self-rated health and experience of cancer, and weighting for non-representativeness, made little difference to the pattern of results.

The Broselow tape, like other one-dimensional length-based systems, is vulnerable to error based on individual variations of weight-for-length (differences in body habitus) [56 59].

A weight-for-age difference of >0.67 SD has been defined as a clinically relevant rapid weight gain in infancy associated with a risk of obesity later in childhood [ 14].

However, we implemented inverse probability censoring weighting to account for differences in measured characteristics between the baseline and follow-up samples.

Prescriptions from unsampled stores were estimated on the basis of prescription totals from matched nearby stores with weighting to adjust for differences in total retail sales volume, which was available for nearly all stores.

Oestradiol and α-foetoprotein were measured from umbilical plasma, and birth weight was standardized as the ratio between the observed and expected birth weight, adjusted for differences in gestation length and offspring sex.

First, we described the sample characteristics for each country using DHS sample weights, adjusting for differences in the probability of selection from the survey design.

Recalibration of the sampling weights corrects for differences in missing data across age, sex, and race/ethnicity strata, and assumes that data within strata are missing at random.

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