Question 1

What does the Estimates of Covariance Parameters table tell you about the data?   Source: http:/ / www2.sas.com/ proceedings/ sugi31/ 151-31.pdf

Accepted Answer

A)  Effect size 
B)  Random effects 
C)  Variance 
D) None of the above 
A)  Effect size 
B)  Random effects 
C)  Variance 
D) None of the above B

Question 2

At age 23, what was the average physical health score of the young adults?

Accepted Answer

A)  70.95 
B)  72.26 
C)  74.71 
D)  75.19 
A)  70.95 
B)  72.26 
C)  74.71 
D)  75.19 C

Question 3

In a study of the analysis of large hierarchical data with multilevel logistic modelling using PROC Glimmix, Li et al. determine the following results in their first approach to the analysis when considering factors associated with death from injury and exposure, gender, race or age   Source: http:/ / www2.sas.com/ proceedings/ sugi31/ 151-31.pdf
What would you consider to be the findings of this result?

Accepted Answer

A)  No significant association between death from injury and gender. 
B)  No significant association between death from injury and race. 
C)  A significant association between death from injury and exposure. 
D)  No significant association between death from injury and age. 
A)  No significant association between death from injury and gender. 
B)  No significant association between death from injury and race. 
C)  A significant association between death from injury and exposure. 
D)  No significant association between death from injury and age. C

Question 4

In a study of the Analysis of Large Hierarchical Data with Multilevel Logistic modelling using PROC Glimmix, Li et al determine the following results in their first approach to the analysis when considering factors associated with death from injury and exposure, gender, race or age   Source: http:/ / www2.sas.com/ proceedings/ sugi31/ 151-31.pdf
In their second round of analysis, a range of data outputs were achieved including the following table
  Source: http:/ / www2.sas.com/ proceedings/ sugi31/ 151-31.pdf
What do the data represent?

Accepted Answer

A)  They tell whether predictors significantly predict the outcome, and in this example the predictor of exposure is not significant. 
B)  They tell whether predictors significantly predict the outcome, and in this example the predictor of gender is not significant. 
C)  They tell whether predictors significantly predict the outcome, and in this example the predictor of race is not significant. 
D)  They tell whether predictors significantly predict the outcome, and in this example the predictor of age is not significant. 
A)  They tell whether predictors significantly predict the outcome, and in this example the predictor of exposure is not significant. 
B)  They tell whether predictors significantly predict the outcome, and in this example the predictor of gender is not significant. 
C)  They tell whether predictors significantly predict the outcome, and in this example the predictor of race is not significant. 
D)  They tell whether predictors significantly predict the outcome, and in this example the predictor of age is not significant.

Question 5

Which of the following is not an example of the benefits of multilevel models?

Accepted Answer

A)  No assumptions of homogeneity of regression slope 
B)  No assumptions of independence 
C)  No issue with missing data 
D)  No assumption of interaction 
A)  No assumptions of homogeneity of regression slope 
B)  No assumptions of independence 
C)  No issue with missing data 
D)  No assumption of interaction

What does the Estimates of Covariance Parameters table tell you about the data? Source: http:/ / www2.sas.com/ proceedings/ sugi31/ 151-31.pdf

At age 23, what was the average physical health score of the young adults?

Which of the following is not an example of the benefits of multilevel models?

Why Is My Evil Lecturer Forcing Me to Learn Statistics

The Spine of Statistics

The Phoenix of Statistics

The Ibm Spss Statistics Environment

Exploring Data With Graphs

The Beast of Bias

Non-Parametric Models

Correlation

Regression

Comparing Two Means

Moderation,mediation and More Regression

Glm 1: Comparing Several Independent Means

Glm 2: Comparing Means Adjusted for Other Predictors Analysis of Covariance

Glm 3: Factorial Designs

Glm 4: Repeated-Measures Designs

Glm 5: Mixed Designs

Multivariate Analysis of Variance Manova

Exploratory Factor Analysis

Categorical Outcomes: Chi-Square and Loglinear Analysis

Categorical Outcomes: Logistic Regression

Filters

Exam 21: Multilevel Linear Models

What does the Estimates of Covariance Parameters table tell you about the data? Source: http:/ / www2.sas.com/ proceedings/ sugi31/ 151-31.pdf

At age 23, what was the average physical health score of the young adults?

Which of the following is not an example of the benefits of multilevel models?

Why Is My Evil Lecturer Forcing Me to Learn Statistics

The Spine of Statistics

The Phoenix of Statistics

The Ibm Spss Statistics Environment

Exploring Data With Graphs

The Beast of Bias

Non-Parametric Models

Correlation

Regression

Comparing Two Means

Moderation,mediation and More Regression

Glm 1: Comparing Several Independent Means

Glm 2: Comparing Means Adjusted for Other Predictors Analysis of Covariance

Glm 3: Factorial Designs

Glm 4: Repeated-Measures Designs

Glm 5: Mixed Designs

Multivariate Analysis of Variance Manova

Exploratory Factor Analysis

Categorical Outcomes: Chi-Square and Loglinear Analysis

Categorical Outcomes: Logistic Regression

Filters