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We then tested for significant theta modulation through sliding multivariate regression with temporal cluster correction (see Methods).
Three key steps of the strategy are as follows: (1) remove baselines of the chromatograms; (2) align retention time; (3) conduct quantitative analysis using multivariate regression with entire chromatographic profiles.
Here, we test if the combination of logistic multivariate regression with Markov chains, however, allows for spatially distributed transitions probabilities based on abiotic factors and therefore, it is able to reproduce the preferential colonization of the most favourable locations.
The framed hypotheses are tested using multivariate regression with ordinary least square, i.e., linear regression estimation.
For regression of shape on size we used ordinary least squares multivariate regression with MANOVA testing.
Data were analysed as a two level, mixed, multivariate regression with indicator crossed with practice.
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We ran multivariate regressions with the same covariates we defined in the complete-case analysis.
As further analysis with the same database, we conducted a propensity score matching analysis and fixed effects, multivariate regressions with propensity score weighting.
We then performed six multivariate regressions with the full set of independent variables for each of the health services, using separate doctor and nurse concentrations as well as aggregate health workers.
We will test the association with stunting using multivariate regression models, with linear growth as the outcome variable and mycotoxin exposure as the independent variable.
Logistic regression was used to perform both univariate (regression model with one independent variable) and multivariate (regression model with more than one independent variable) analyses.
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