Results 221 to 230 of about 2,215,776 (276)
Arthritis Care &Research, EarlyView.Objective We developed a novel electronic health record sidecar application to visualize key rheumatoid arthritis (RA) outcomes, including disease activity, physical function, and pain, via a patient‐facing graphical interface designed for use during outpatient visits (“RA PRO dashboard”).
Gabriela Schmajuk +16 more
wiley +1 more source
Variable parameters memory-type control charts for simultaneous monitoring of the mean and variability of multivariate multiple linear regression profiles. [PDF]
Sci RepSabahno H, Eriksson M.
europepmc +1 more source
Prevalence of dyslipidaemia within Polish nurses. Cross-sectional study - single and multiple linear regression models and ROC analysis. [PDF]
BMC Public HealthBartosiewicz A +5 more
europepmc +1 more source
COVID-19 vaccine intercountry distribution inequality and its underlying factors: a combined concentration index analysis and multiple linear regression analysis. [PDF]
Front Public HealthAbu El Kheir-Mataria W +3 more
europepmc +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
2011
The main purpose of this chapter is to predict the value of some variable Y based on a given set of variables X i where i = 1, 2, …, p − 1 and p is an integer larger than or equal to 2. The following example will be examined in detail throughout this chapter.
+5 more sources
The main purpose of this chapter is to predict the value of some variable Y based on a given set of variables X i where i = 1, 2, …, p − 1 and p is an integer larger than or equal to 2. The following example will be examined in detail throughout this chapter.
+5 more sources
2017
In the previous chapter, we discussed situations where we had only one independent variable (X ) and evaluated its relationship with a dependent variable (Y ). This chapter goes beyond that and deals with the analysis of situations where we have more than one X (predictor) variable, using a technique called multiple regression.
Paul D. Berger +2 more
+5 more sources
In the previous chapter, we discussed situations where we had only one independent variable (X ) and evaluated its relationship with a dependent variable (Y ). This chapter goes beyond that and deals with the analysis of situations where we have more than one X (predictor) variable, using a technique called multiple regression.
Paul D. Berger +2 more
+5 more sources
2014
This chapter provides an overview of multiple linear regression, a statistical technique that predicts values of a quantitative dependent variable from values of two or more independent variables. By including more than one independent variable, a multiple linear regression can often account for more variability in the dependent variable than can a ...
William H. Holmes, William C. Rinaman
openaire +2 more sources
This chapter provides an overview of multiple linear regression, a statistical technique that predicts values of a quantitative dependent variable from values of two or more independent variables. By including more than one independent variable, a multiple linear regression can often account for more variability in the dependent variable than can a ...
William H. Holmes, William C. Rinaman
openaire +2 more sources
2012
Chapters 13 and 14 examined in detail the simple regression model with one independent variable (such as amount of fertilizer) and one dependent variable (such as yield of corn). In many cases, however, more than one factor can affect the outcome under study. In addition to fertilizer, rainfall and temperature certainly influence the yield of corn.
Cheng-Few Lee, John C. Lee, Alice C. Lee
+4 more sources
Chapters 13 and 14 examined in detail the simple regression model with one independent variable (such as amount of fertilizer) and one dependent variable (such as yield of corn). In many cases, however, more than one factor can affect the outcome under study. In addition to fertilizer, rainfall and temperature certainly influence the yield of corn.
Cheng-Few Lee, John C. Lee, Alice C. Lee
+4 more sources