Sentence examples for most significant lag from inspiring English sources

In Seattle, the most significant lag time was 10 years for both the crude (p-value = 0.20) and the adjusted (p-value = 0.15) models.

Using the most significant lag time identified in crude and adjusted models, we found significant clusters of elevated NHL risk in three of the study centers (Detroit, Iowa, and Los Angeles).

Because the choice of the lag was a critical step, we performed additional analyses using, for all the studies, the effect estimate at lag 0 1 (instead of the most significant lag).

Only these four lagged parameters were evaluated as potential covariate predictors in the subsequent model development; the others were excluded because of either large colinearity within their group (G32DAYS with TAVG) (Table 3) or their most significant lag being more interseasonal (L18DAYS at the biweekly equivalent of 3 4 months).

In our analysis of residential locations at several time periods, the most significant lag time was 20 years according to both crude and adjusted models (Table 3) in three centers: Detroit (crude and adjusted models p-value = 0.07), Iowa (crude model p-value = 0.21, adjusted model p-value = 0.14), and Los Angeles (crude model p-value = 0.003, adjusted model p-value = 0.03).

Low temperature did not have a clear effect at lag 0 but significantly increased CVD admission risk at lag 4, lag 7 (most significant), and lag 14, whereas high temperature reduced CVD admission risk at lag 0 and increased the risk of CVD admission at lag 4, lag 7, and lag 14 (but not significant).

Sixth, all possible combinations of the most significant independent lagged parameters were incorporated into the appropriate ARIMA models using transfer functions and then evaluated for goodness of fit.

This association was highest for respiratory mortality in S/C de Tenerife, with positive coefficients for the various lags analyzed and with the most significant estimate at lag 2 for the two fractions.

However, in most cases, there is significant lag in the publication of peer-reviewed articles concerning ADEs.

Correlations were highest and most significant when no time lags were included in the models.

Cross-correlation analysis showed that several evaluated weather parameters were significantly associated with DPOP at various biweekly lags, but the most significant associations (within each meteorological group from Table 1) were for TAVG, ΔTAVG, and RHAVG at a 1-biweek lag and RRTOT at a 2-biweek lag (Table 2).