response variable

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response variable

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1. (Mathematics) statistics a more modern term for dependent variable2
2. (Psychology) statistics a more modern term for dependent variable2
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The horizontal axis represents quarters whereas the vertical axis represents the units of response variables. Source: Authors calculation based on data from Central Bank of Iceland (2018) and Statistics Iceland (2018)
The response variables are associated with statistical distributions linking the events to their respective probabilities.
Covariates are variables that are known or expected to be related to the response variables of interest.
Survival rate (SR), growth rate (GR), feed conversion ratio (FCR), and protein efficiency ratio (PER) was the response variables used to evaluate the feeds supplied.
The influence of designed formulations on response variables (texture parameters), firmness, cohesiveness, consistency, and index of viscosity, was evaluated.
Assessment of response variables, treadmill exercise time, stress echo score, symptom frequency, and angina severity were performed at pre-randomisation and blinded follow-up.
To compute the importance of relevant gene in a dataset, One-Way-ANOVA based on p-value was used as a technique to analyze the colon cancer data, in which one or more response variables are measured under various conditions identified by one or more classification variables.
CHAID algorithm uses chi-square test for the categorical response variables (Agresti, 1990), while it uses F test for continuous one (Orhan et al., 2016).
Our strategy relies on a new tool, the multivariate ordered logit, designed to study how the joint distribution of two or more ordered response variables depend on exogenous covariates.
All the methods used here are supervised learning techniques, which use their own algorithms to generate rules that best explain the response variables.
The generalized linear mixed models were used to analyze the response variables. The most parsimonious model for each of the response variables was selected by Akaike Information Criterion (AIC).
Multitarget regression trees (MTRTs) predict several numeric response variables simultaneously [29] and offer several advantages over STRTs.
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