Results 131 to 140 of about 1,274,632 (180)
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1978
In the two preceding chapters we have set forth, in some detail, the estimation of parameters and the properties of the resulting estimators in the context of the standard GLM. We recall that rather stringent assumptions were made relative to the error process and the explanatory variables.
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In the two preceding chapters we have set forth, in some detail, the estimation of parameters and the properties of the resulting estimators in the context of the standard GLM. We recall that rather stringent assumptions were made relative to the error process and the explanatory variables.
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2020
Second-level analyses allow researchers to make inferences about properties of groups or populations, by generalizing from the observations of only a subset of subjects in a study. This chapter describes the mathematics behind the General Linear Model (GLM), the approach used in CONN for all second-level analyses of functional connectivity measures ...
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Second-level analyses allow researchers to make inferences about properties of groups or populations, by generalizing from the observations of only a subset of subjects in a study. This chapter describes the mathematics behind the General Linear Model (GLM), the approach used in CONN for all second-level analyses of functional connectivity measures ...
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2012
A new program for depression is instituted in the hopes of reducing the number of visits each patient makes to the emergency room in the year following treatment. Predictors include (among many others) treatment (yes/no), race, and drug and alcohol usage indices.
Eric Vittinghoff +3 more
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A new program for depression is instituted in the hopes of reducing the number of visits each patient makes to the emergency room in the year following treatment. Predictors include (among many others) treatment (yes/no), race, and drug and alcohol usage indices.
Eric Vittinghoff +3 more
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The American Statistician, 1994 Integrative oncology: Addressing the global challenges of cancer prevention and treatment
Ca-A Cancer Journal for Clinicians, 2022Jun J Mao,, Msce +2 more
exaly
2009
The general linear model incorporates many of the most popular and useful models that arise in applied statistics, including models for multiple regression and the analysis of variance. The basic model can be written succinctly in matrix form as $$Y = X\beta + \epsilon,$$ (14.1) where Y, our observed data, is a random vector in \(\mathbb{R}^n,
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The general linear model incorporates many of the most popular and useful models that arise in applied statistics, including models for multiple regression and the analysis of variance. The basic model can be written succinctly in matrix form as $$Y = X\beta + \epsilon,$$ (14.1) where Y, our observed data, is a random vector in \(\mathbb{R}^n,
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1998
Abstract The data in Table 4.1 are pairs of measurements of body weights and diastolic blood pressures recorded on 34 heavy men. Even with as few as 34 observations, it is useful to summarize the relationship between two variables.
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Abstract The data in Table 4.1 are pairs of measurements of body weights and diastolic blood pressures recorded on 34 heavy men. Even with as few as 34 observations, it is useful to summarize the relationship between two variables.
openaire +1 more source