Estimating Models Using Dummy Variables

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Estimating Models Using Dummy Variables

Name:
Institution:

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Research topic: Use of Mobile Phones to Remind Patients on Taking Medicine and Appointments

 

 

Descriptive Statistics
  Mean Std. Deviation N
Do you use mobile health technologies to provide health services to patients? 1.25 .444 20
How do you rate the folllowing cost factors? 1.30 .470 20
Application used to support health services 2.45 1.317 20

 

 

 

 

 

 

 

Coefficients
Model Unstandardized Coefficients Standardized Coefficients t Sig. Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) 1.058 .355   2.982 .008    
How do you rate the following cost factors? .113 .228 .120 .496 .626 .988 1.012
Application used to support health services .018 .082 .054 .224 .825 .988 1.012
a. Dependent Variable: Do you use mobile health technologies to provide health services to patients?

 

 

 

 

 

 

 

 

 

Collinearity Diagnostics
Model Dimension Eigenvalue Condition Index Variance Proportions
(Constant) How do you rate the following cost factors? Application used to support health services
1 1 2.788 1.000 .01 .01 .02
2 .159 4.191 .04 .19 .88
3 .053 7.245 .95 .80 .10
a. Dependent Variable: Do you use mobile health technologies to provide health services to patients?

 

 

 

ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression .070 2 .035 .163 .851b
Residual 3.680 17 .216    
Total 3.750 19      
a. Dependent Variable: Do you use mobile health technologies to provide health services to patients? (abmax)
b. Predictors: (Constant), Application used to support health services (App), How do you rate the following cost factors? (Rate)

 

In the prediction of (abmax) from (App), (Rate): the regression equation can be generally represented as:

Predicted (App) = 1.058 – (.113 x App) – (.018 x Rate)

 

 

Assumption

There can be “two or more independent variables, which can either be continuous (i.e., an interval or ratio variable) or categorical (i.e., an ordinal or nominal variable)” (Laerd Statistics, n.d.).  For instance nominal variables can be in 2 gender groups: men and women, or five professional groups like: therapists, nurses, physicians, dentists, and so wardens. Variables are of different types. An independent variable being dichotomous makes it a moderating variable, and this calls for the need of conducting a Dichotomous moderator analysis. This assumption has been met in the above case. However, in case of a violation of this assumption, the only remedy is changing all the variable considered.

 

 

 

 

 

 

 

 

 

 

 

 

References

Laerd Statistics. (n.d.). Multiple Regression Analysis using SPSS Statistics. Retrieved from Laerd Statistics: https://statistics.laerd.com/spss-tutorials/multiple-regression-using-spss-statistics.php

 

 

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