Sentence examples for more complex regression from inspiring English sources

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Only then should you move onto two, three, or more variables and more complex regression models.

The nonnegative garrote method is a powerful variable selection method, developed originally for linear regression but recently successfully extended to more complex regression models.

Simple analyses such as t tests or more complex regression analyses will be undertaken.

However, it should be noted that the Finnish sample is also the smallest, and may thus have insufficient power in the more complex regression models.

In their article they dismissed the linear regression model, because in the more complex regression scenarios they were considering it could lead to inadmissible predictions (e.g. predicted values outside of (0,1)).

Finally, while it is beyond the scope of this paper to discuss more complex regression methods, an even more rigorous approach could use generalized linear models to model nonlinear relationships between student characteristics and test scores, analyze student responses at the individual-question level, or produce unbiased estimates in the presence of a ceiling effect.

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More complex multiple regression analysis would be required to separate correlations that reflect true causality; for the purposes of this paper, we felt it was sufficient to note the strongest correlations.

This simple analysis was then extended with a more complex multivariate regression model with the infant mortality ratio as the dependent variable and all four factors as independent ones, taking into consideration the presence of the correlated data (time-repeated measurements of 7 years of observation).

Given the short time frame and full follow-up of patients completing treatment, we used the proportion of subjects with any fall or any injurious fall in our analysis rather than the more complex negative binomial regression model recommended for longer-term studies with loss to follow-up [ 20].

For example, we tested regression models more complex than log-linear, simple linear regression without logarithmic transformations and different versatility measures (NTRP or NCO) than the number of neighbours (NN).

describe how such more complex types of nonlinear regression can be calculated in R using the function optim.

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