Examples of using Multiple linear regression model in English and their translations into Portuguese
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Colloquial
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Official
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Medicine
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Financial
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Ecclesiastic
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Ecclesiastic
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Computer
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Official/political
Data were analyzed using descriptive statistics and multiple linear regression model by ordinary least squares ols.
The multiple linear regression model, when investigating the relation of anxiety symptoms with sex
The multiple linear regression model, when investigating the relation between depression symptoms with the same variables, provided a similar result to that from anxiety symptoms.
Factors associated with QoL were identified using a multi-variable analysis of the multiple linear regression model enter method, considering a level of significance of 5% p< 0.05.
A multiple linear regression model was developed to evaluate the"duration of surgery,""length of hospital stay" and"total cost" outcomes.
A multiple linear regression model was adjusted in order to analyze the impact of some clinical
The multiple linear regression model adjusted for age,
A multiple linear regression model was built, considering as dependent variable the standard deviation of mean scores of pain attributed by the adult physician,
Finally, a multiple linear regression model was adjusted to simultaneously verify which of the variables chosen influenced the KI on PIM.
Table 2 presents the final multiple linear regression model and shows the independent variables statistically related to the social relationships domain,
It was used a multiple linear regression model with backward selection method,
The residual analysis of the multiple linear regression model showed a residual dispersion suggesting a non-random distribution.
A multiple linear regression model was performed,
The multiple linear regression model that was developed for the entire sample was also applied in the analysis of each stratum.
Besides that, a multiple linear regression model was performed in order to check for the influence of variables gender,
it is concluded that the Multiple Linear Regression model is valid.
Pearson's correlation coefficient and a multiple linear regression model were utilized to test these associations.
For a multiple linear regression model using these expenses
From a practical perspective, the multiple linear regression model, which was adjusted to the data in Table 1,
Besides the comparisons involving the non-parametric tests, a multiple linear regression model was applied for the variable"duration of naps" with regard to the other co-variables, except for the frailty criteria.