Estimating Models Using Dummy Variables

Name:

Institution:

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

Descriptive Statistics |
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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 |
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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 |
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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? |

ANOVA^{a} |
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Model | Sum of Squares | df | Mean Square | F | Sig. | |

1 | Regression | .070 | 2 | .035 | .163 | .851^{b} |

Residual | 3.680 | 17 | .216 | |||

Total | 3.750 | 19 | ||||

a. Dependent Variable: Do you use mobile health technologies to provide health services to patients? (ab_{max}) |
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b. Predictors: (Constant), Application used to support health services (App), How do you rate the following cost factors? (Rate) |

In the prediction of (ab_{max}) 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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