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Therefore, in classes of older children variance between observations is guaranteed, while in the case of younger children an important variance is also guaranteed due to the fact that the age range within a class, although small, is strong enough to mean that the intra-class correlation is not very large.
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The overall model was statistically significant, F 3, 93) = 11.8, p < .00001, and accounted for 25.24% (adjusted r 2 ) of transformed-number-of-children variance.
Results: Within-child variance exceeded between-child variance by a factor of two to eight, depending on metabolite grouping.
Further, within-child variance was approximately two to three times the between-child variance for total DAP metabolites (e.g., 66% vs. 34% for FMV samples for creatinine-adjusted total DAPs, ICC = 0.27 0.35).
Constraining this between-child variance within each latent class to be zero results in a special type of growth mixture model called a latent class growth model.
Reproducibility of creatinine-adjusted DE metabolites was much lower (ICCs = 0.11 0.16) (Table 3), and within-child variance exceeded between-child variance between a factor between five (e.g., 57% vs. 12% of the total variance for non-FMV spot samples) and eight (e.g., 88% vs. 12% of the total variance for FMV spot samples) for these metabolites.
The geometric mean for the population was designated μ, and a components-of-variance analysis was used to estimate a) the overall mean of the log-transformed values, log; b) the between-child variance of log-transformed child-specific mean values, σP; and c) the within-child variance of log-transformed levels, σI.
Longitudinal measurements indicate that between-child variance was greater than within-child variance for two VOCs (benzene, toluene), for both heavy metals (Pb, Hg), for all detectable OC pesticides, and for 15 of the measured PCB congeners (74, 99, 101, 118, 138 158, 146, 153, 156, 170, 178, 180, 187, 189, 194, 195).
We used mixed random-effects models to compute the between-child and within-child variance for 24-hr samples from days 2 and 5, and for all FMV spot samples.
Overall, the high within-child variance, the weak correlation across days, and low specificity suggests that single-day measurements may not adequately characterize exposure for longer time frames necessary for chronic risk assessments or epidemiologic studies.
A sensitivity analysis limited to the most complete 24-hr samples (based on five or more spot samples) indicated even greater within-child variance (for total DAPs, 77% of total, ICC = 0.23; data not shown).
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