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Multiple Regression—Regression Diagnostics
2004In Chapter 9 we show how to set up and produce an initial analysis of a regression model with several predictors. In the present chapter we discuss ways to investigate whether the model assumptions are met and, when the assumptions are not met, ways to revise the model to better conform with the assumptions. We also examine ways to assess the effect on
Richard M. Heiberger, Burt Holland
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2007
This chapter describes multiple linear regression, a statistical approach used to describe the simultaneous associations of several variables with one continuous outcome. Important steps in using this approach include estimation and inference, variable selection in model building, and assessing model fit.
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This chapter describes multiple linear regression, a statistical approach used to describe the simultaneous associations of several variables with one continuous outcome. Important steps in using this approach include estimation and inference, variable selection in model building, and assessing model fit.
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1983
In this chapter we will apply the matrix algebra of the previous chapter to multiple regression. We assume that the reader has had at least a beginning exposure to the idea of multiple regression. In multiple regression we explore the relationship of a single dependent variable to a set of p independent variables.
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In this chapter we will apply the matrix algebra of the previous chapter to multiple regression. We assume that the reader has had at least a beginning exposure to the idea of multiple regression. In multiple regression we explore the relationship of a single dependent variable to a set of p independent variables.
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Antibody–drug conjugates: Smart chemotherapy delivery across tumor histologies
Ca-A Cancer Journal for Clinicians, 2022Paolo Tarantino +2 more
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