magine that you, a social psychologist, study people living with HIV. You are interested in the relationship between viral load, the amount of HIV in a sample of blood, and perceived stigma, the amount people with HIV perceive others to hold stigmatizing views about their condition. You have 100 people with HIV complete a perceived stigma scale, as well as provide a sample of blood, so their viral load can be measured. You run a regression analysis using the data you’ve collected to see whether perceived stigma can be predicted based on viral load. The output from the analysis is presented below: How much does the estimate of perceived stigma change if viral load increases by one unit?

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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Imagine that you, a social psychologist, study people living with HIV. You are interested in the relationship between viral load, the amount of HIV in a sample of blood, and perceived stigma, the amount people with HIV perceive others to hold stigmatizing views about their condition. You have 100 people with HIV complete a perceived stigma scale, as well as provide a sample of blood, so their viral load can be measured. You run a regression analysis using the data you’ve collected to see whether perceived stigma can be predicted based on viral load. The output from the analysis is presented below:

How much does the estimate of perceived stigma change if viral load increases by one unit?

Regression
Variables Entered/Removed"
Variables
Removed
Model
Variables
Entered
ViralLoad2b
a. Dependent Variable: PerceivedStigma2
b. All requested variables entered.
Model
1
Model
1
a. Predictors: (Constant), ViralLoad2
R
.787²
Model
1
Regression
Residual
Model Summary
Adjusted R
Square
R Square
.619
Sum of
Squares
Method
Enter
46.091
28.409
74.500
.571
ANOVA
Total
a. Dependent Variable: PerceivedStigma2
b. Predictors: (Constant), ViralLoad2
1.989
.074
df
1
8
(Constant)
ViralLoad2
a. Dependent Variable: PerceivedStigma2
9
Std. Error of
the Estimate
1.884
Unstandardized Coefficients
B
Std. Error
Coefficients
Mean Square
46.091
3.551
1.142
.021
Standardized
Coefficients
Beta
.787
F
12.979
t
1.741
3.603
Sig.
.007b
Sig.
.120
.007
Transcribed Image Text:Regression Variables Entered/Removed" Variables Removed Model Variables Entered ViralLoad2b a. Dependent Variable: PerceivedStigma2 b. All requested variables entered. Model 1 Model 1 a. Predictors: (Constant), ViralLoad2 R .787² Model 1 Regression Residual Model Summary Adjusted R Square R Square .619 Sum of Squares Method Enter 46.091 28.409 74.500 .571 ANOVA Total a. Dependent Variable: PerceivedStigma2 b. Predictors: (Constant), ViralLoad2 1.989 .074 df 1 8 (Constant) ViralLoad2 a. Dependent Variable: PerceivedStigma2 9 Std. Error of the Estimate 1.884 Unstandardized Coefficients B Std. Error Coefficients Mean Square 46.091 3.551 1.142 .021 Standardized Coefficients Beta .787 F 12.979 t 1.741 3.603 Sig. .007b Sig. .120 .007
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