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Approximately 20% of all cases were missing pollutant data for lags of interest.
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To examine whether a change in an outcome (e.g., increased TpTe) associated with one pollutant (e.g., AMP lagged 24 47) was independent of a second pollutant (UFP or PM2.5) at the same lag time, we used the same model described above (same covariates and correlation structure as single-pollutant model) including both pollutants at the lag time of interest (e.g., AMP and UFP counts lagged 24 47 hr).
The turn of the century could easily see a global boom resulting from the lagged effects of interest rate cuts and monetary stimulus around the world.
Previous cluster studies [ 26- 28] using generalized additive models included in one model all possible residences for each subject before a lag time of interest, resulting in a biased model with several correlated records per subject.
Specifically, we estimated equation (1) for time at diagnosis (Z0) and for each lag time of interest (Z k ) and statistically tested the deviances from the models with a Z term and the deviance from the model with no Z term.
Lag phase is also of interest in fields such as food safety- in which lag phase is one factor in determining food shelf life [ 4- 6].
To account for overdispersion (deviance = 2.39 in the final model) in the norovirus report data, standard errors were scaled using square root of Pearson chi-squared goodness of fit statistic.[17] The model was built in a stepwise fashion by first constructing the confounder model, then adding the variables of interest (lagged weather variables, population immunity, new virus variants).
First, identification, confirmation and notification of H1N1 cases is unlikely to have been perfect given the mild and self-limiting nature of most infections, and dates of importation and local transmission that we report may lag behind the true events of interest.
Of interest, the time lag between the last dose of bisphosphonate and initiation of teriparatide positively influenced the response to teriparatide.
When Zulily went public in 2013, it sparked a resurgence of interest in an otherwise lagging e-commerce market.
We account for endogeneity through the use of multiple lagged independent variables, specifically regarding our main variable of interest, immigration flows.
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