Sentence examples for missing data significantly from inspiring English sources

A high proportion of missing data significantly decreases the sample size available for statistical analysis, and consequently decreases statistical power.

Those participants with missing data were significantly more likely to be male and had significantly higher healthcare costs during the baseline data collection period (the ten weeks immediately prior to the commencement of the intervention).

The evaluation of the methods here is much more comprehensive than previous studies, as it uses much longer air quality time series with no missing data, under significantly larger number missing data scenarios.

For the Loekito score, patients with missing data had significantly lower 1-day mortality (table 5).

The proportion of cases with missing data decreased significantly over the study period from 15.5 to 9.5% (P=0.0109).

Those who were missing data were significantly younger (11.0 vs. 12.3 y; P < 0.01), had a higher BMI (25.2 vs. 23.1; P < 0.04) than those with full data while there was no difference in BMI percentile (80th vs. 73rd; P = 0.55).

For one, Gale et al 2 and Hatch et al 3 tested binary logistic regression models in the British Cohort Studies 1946 , 1958and 1970 with list-wise omission of cases with missing data, which significantly reduced sample sizes by more than half (eg, the British Cohort Study 1970 included initially about 17 200 people, but only 6074 were included in the analysis sample 2).

Statistical methods to solve the problem of missing data have improved significantly, as demonstrated by Schafer and Graham (2002), although misconceptions still remain abundant.

The proportion of missing data was not significantly different between asthma and non-asthma groups.

Demographics of participants with missing data did not significantly differ from the rest of the sample.

Having missing data did not significantly influence the outcome in the derivation cohort (OR 1.12, 95% CI 0.56 to 2.41).