Question 1

If a lack of linearity is identified as an issue, how might you address this?

Accepted Answer

A)  Transform the data. 
B)  Change the test to a chi-square test. 
C)  Linearity is not important within multilevel analysis. 
D)  Conduct group mean centring. 
A)  Transform the data. 
B)  Change the test to a chi-square test. 
C)  Linearity is not important within multilevel analysis. 
D)  Conduct group mean centring. A

Question 2

Group mean centring is a useful way to prevent multicollinearity, but how is it usually calculated?

Accepted Answer

A)  An individual score (player confidence) is subtracted from a group mean (mean player confidence in that group). 
B)  An individual score (player confidence) is multiplied by the group mean (mean player confidence in that group). 
C)  An individual score (player confidence) is added to a group mean (mean player confidence in that group). 
D)  An individual score (player confidence) is divided by a group mean (mean player confidence in that group). 
A)  An individual score (player confidence) is subtracted from a group mean (mean player confidence in that group). 
B)  An individual score (player confidence) is multiplied by the group mean (mean player confidence in that group). 
C)  An individual score (player confidence) is added to a group mean (mean player confidence in that group). 
D)  An individual score (player confidence) is divided by a group mean (mean player confidence in that group). A

Question 3

Based on a multilevel analysis, a chi-square value of 7.05 was obtained at one degree of freedom. What could be concluded from this finding?

Accepted Answer

A)  The change is not significant. 
B)  The change is significant at the .10 level. 
C)  The change is significant at the .05 level. 
D)  The change is significant at the .01 level. 
A)  The change is not significant. 
B)  The change is significant at the .10 level. 
C)  The change is significant at the .05 level. 
D)  The change is significant at the .01 level. D

Question 4

What is a second-order polynomial also known as?

Accepted Answer

A)  Linear 
B)  Quadratic 
C)  Cubic 
D)  Binomial 
A)  Linear 
B)  Quadratic 
C)  Cubic 
D)  Binomial

Question 5

A researcher wanted to investigate the confidence levels of athletes in different athletics clubs. In addition, he wanted to see whether the athletes' coaches had an influence and whether this varied from country to country. How many levels would be involved in this analysis?

Accepted Answer

A)  3 
B)  4 
C)  5 
D)  6 
A)  3 
B)  4 
C)  5 
D)  6

Question 6

Which of the following descriptions best applies to this graph?

Accepted Answer

A)  Fixed intercept, random slope 
B)  Fixed intercept, fixed slope 
C)  Random intercept, random slope 
D)  Random intercept, fixed slope 
A)  Fixed intercept, random slope 
B)  Fixed intercept, fixed slope 
C)  Random intercept, random slope 
D)  Random intercept, fixed slope

Question 7

One of the issues with multilevel linear analysis is that it introduces dependency between the contextualized variables (e.g. the influence of different coaches on their athletes' confidence), but what does this mean?

Accepted Answer

A)  Residuals within the model will be correlated. 
B)  The variables are from different cases and therefore make the model unstable. 
C)  Independence of the different levels makes the analysis more prone to Type I error. 
D)  The experimental nature of the research design implies that the contextualized variables will differ at each level of the model. 
A)  Residuals within the model will be correlated. 
B)  The variables are from different cases and therefore make the model unstable. 
C)  Independence of the different levels makes the analysis more prone to Type I error. 
D)  The experimental nature of the research design implies that the contextualized variables will differ at each level of the model.

Question 8

Suppose you were interested in the development of player confidence when exposed to structured coaching sessions. What is the name of the model that examines the rate of development or change in a given variable (e.g. confidence)?

Accepted Answer

A)  Growth model 
B)  Seismic model 
C)  Formulation model 
D)  Analysis model 
A)  Growth model 
B)  Seismic model 
C)  Formulation model 
D)  Analysis model

Question 9

Which of the following would not be expected to change with time?

Accepted Answer

A)  Attitude towards training 
B)  Gender of participants 
C)  Anxiety prior to competition 
D)  Cellular mitochondria density during aerobic training 
A)  Attitude towards training 
B)  Gender of participants 
C)  Anxiety prior to competition 
D)  Cellular mitochondria density during aerobic training

Question 10

Sports and exercise science related research frequently uses small sample groups. Therefore, when applying a multilevel analysis technique it is necessary to calculate the log-likelihood value. SPSS produces four versions of the calculation, but which of the following would be most appropriate to use when sample sizes are small?

Accepted Answer

A)  Hurvich and Tsai's criterion (AIC
C)  
B)  Akaike's information criterion (AI
C)  
C)  Bozdogan's criterion (CAI
C)  
D)  Schwarz's Bayesian criterion (BI
C)  
A)  Hurvich and Tsai's criterion (AIC
C)  
B)  Akaike's information criterion (AI
C)  
C)  Bozdogan's criterion (CAI
C)  
D)  Schwarz's Bayesian criterion (BI
C)

Question 11

Which of the following descriptions best applies to this graph?

Accepted Answer

A)  Fixed intercept, random slope 
B)  Fixed intercept, fixed slope 
C)  Random intercept, random slope 
D)  Random intercept, fixed slope 
A)  Fixed intercept, random slope 
B)  Fixed intercept, fixed slope 
C)  Random intercept, random slope 
D)  Random intercept, fixed slope

Question 12

Where would you position the club (i.e. what level) in the model of Q3?

Accepted Answer

A)  3 
B)  4 
C)  5 
D)  6 
A)  3 
B)  4 
C)  5 
D)  6

Question 13

A covariance structure needs to be applied to multilevel modelling when there are random effects or repeated measures incorporated into the design. These are important as they provide an estimate of the model parameters, but what happens if you apply a covariance structure that is too simple?

Accepted Answer

A)  It increases the likelihood of making a Type I error. 
B)  It increases the likelihood of making a Type II error. 
C)  It increases the likelihood of making a Type I or Type II error. 
D)  It increases the likelihood of accepting the null hypothesis when it is false. 
A)  It increases the likelihood of making a Type I error. 
B)  It increases the likelihood of making a Type II error. 
C)  It increases the likelihood of making a Type I or Type II error. 
D)  It increases the likelihood of accepting the null hypothesis when it is false.

Question 14

Prior to conducting a multilevel analysis, how might you check linearity and any unusual cases (e.g. outlying cases)?

Accepted Answer

A)  Scatterplots 
B)  Bar charts 
C)  Pie charts 
D)  Radar plot 
A)  Scatterplots 
B)  Bar charts 
C)  Pie charts 
D)  Radar plot

Question 15

What is the minimum number of levels required to perform a multilevel linear analysis?

Accepted Answer

A)  2 
B)  3 
C)  4 
D)  5 
A)  2 
B)  3 
C)  4 
D)  5

Question 16

Which of the following is not a form of polynomial curve?

Accepted Answer

A)  Linear 
B)  Quadratic 
C)  Cubic 
D)  Binomial 
A)  Linear 
B)  Quadratic 
C)  Cubic 
D)  Binomial

Question 17

Based on the example above, how many rows are required (in data view) for each individual surveyed in this study for a multilevel analysis to be conducted in SPSS?

Accepted Answer

A)  1 row per person 
B)  2 rows per person 
C)  3 rows per person 
D)  4 rows per person 
A)  1 row per person 
B)  2 rows per person 
C)  3 rows per person 
D)  4 rows per person

Question 18

The UK coaching pyramids in rugby essentially have five levels, with level 1 introducing individuals to coaching, whilst level 5 is tailored for those working at professional clubs or international teams. How would you describe the effects if all five levels were analysed?

Accepted Answer

A)  Fixed effects 
B)  Random effects 
C)  Variable effects 
D)  Intercept effects 
A)  Fixed effects 
B)  Random effects 
C)  Variable effects 
D)  Intercept effects

Question 19

Suppose you were interested in the effect of parental influence (x-axis) on a child's confidence (y-axis) when playing rugby. In addition, you examine the coach's qualifications . What will be the most likely appearance of the intercept and slope?

Accepted Answer

A)  Fixed intercept, random slope 
B)  Fixed intercept, fixed slope 
C)  Random intercept, random slope 
D)  Random intercept, fixed slope 
A)  Fixed intercept, random slope 
B)  Fixed intercept, fixed slope 
C)  Random intercept, random slope 
D)  Random intercept, fixed slope

Question 20

What is the purpose of multilevel linear analysis?

Accepted Answer

A)  To analyse data with a hierarchial structure. 
B)  To analyse data from independent groups. 
C)  To analyse data that are logarithmic. 
D)  To analyse data that are not normally distributed and do not have the assumption of sphericity. 
A)  To analyse data with a hierarchial structure. 
B)  To analyse data from independent groups. 
C)  To analyse data that are logarithmic. 
D)  To analyse data that are not normally distributed and do not have the assumption of sphericity.

If a lack of linearity is identified as an issue, how might you address this?

Group mean centring is a useful way to prevent multicollinearity, but how is it usually calculated?

Based on a multilevel analysis, a chi-square value of 7.05 was obtained at one degree of freedom. What could be concluded from this finding?

What is a second-order polynomial also known as?

A researcher wanted to investigate the confidence levels of athletes in different athletics clubs. In addition, he wanted to see whether the athletes' coaches had an influence and whether this varied from country to country. How many levels would be involved in this analysis?

Which of the following descriptions best applies to this graph?

One of the issues with multilevel linear analysis is that it introduces dependency between the contextualized variables (e.g. the influence of different coaches on their athletes' confidence), but what does this mean?

Suppose you were interested in the development of player confidence when exposed to structured coaching sessions. What is the name of the model that examines the rate of development or change in a given variable (e.g. confidence)?

Which of the following would not be expected to change with time?

Which of the following descriptions best applies to this graph?

Where would you position the club (i.e. what level) in the model of Q3?

A covariance structure needs to be applied to multilevel modelling when there are random effects or repeated measures incorporated into the design. These are important as they provide an estimate of the model parameters, but what happens if you apply a covariance structure that is too simple?

Prior to conducting a multilevel analysis, how might you check linearity and any unusual cases (e.g. outlying cases)?

What is the minimum number of levels required to perform a multilevel linear analysis?

Which of the following is not a form of polynomial curve?

Based on the example above, how many rows are required (in data view) for each individual surveyed in this study for a multilevel analysis to be conducted in SPSS?

The UK coaching pyramids in rugby essentially have five levels, with level 1 introducing individuals to coaching, whilst level 5 is tailored for those working at professional clubs or international teams. How would you describe the effects if all five levels were analysed?

Suppose you were interested in the effect of parental influence (x-axis) on a child's confidence (y-axis) when playing rugby. In addition, you examine the coach's qualifications . What will be the most likely appearance of the intercept and slope?

What is the purpose of multilevel linear analysis?

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

If a lack of linearity is identified as an issue, how might you address this?

Group mean centring is a useful way to prevent multicollinearity, but how is it usually calculated?

Based on a multilevel analysis, a chi-square value of 7.05 was obtained at one degree of freedom. What could be concluded from this finding?

What is a second-order polynomial also known as?

A researcher wanted to investigate the confidence levels of athletes in different athletics clubs. In addition, he wanted to see whether the athletes' coaches had an influence and whether this varied from country to country. How many levels would be involved in this analysis?

Which of the following descriptions best applies to this graph?

One of the issues with multilevel linear analysis is that it introduces dependency between the contextualized variables (e.g. the influence of different coaches on their athletes' confidence), but what does this mean?

Suppose you were interested in the development of player confidence when exposed to structured coaching sessions. What is the name of the model that examines the rate of development or change in a given variable (e.g. confidence)?

Which of the following would not be expected to change with time?

Which of the following descriptions best applies to this graph?

Where would you position the club (i.e. what level) in the model of Q3?

A covariance structure needs to be applied to multilevel modelling when there are random effects or repeated measures incorporated into the design. These are important as they provide an estimate of the model parameters, but what happens if you apply a covariance structure that is too simple?

Prior to conducting a multilevel analysis, how might you check linearity and any unusual cases (e.g. outlying cases)?

What is the minimum number of levels required to perform a multilevel linear analysis?

Which of the following is not a form of polynomial curve?

Based on the example above, how many rows are required (in data view) for each individual surveyed in this study for a multilevel analysis to be conducted in SPSS?

The UK coaching pyramids in rugby essentially have five levels, with level 1 introducing individuals to coaching, whilst level 5 is tailored for those working at professional clubs or international teams. How would you describe the effects if all five levels were analysed?

Suppose you were interested in the effect of parental influence (x-axis) on a child's confidence (y-axis) when playing rugby. In addition, you examine the coach's qualifications . What will be the most likely appearance of the intercept and slope?

What is the purpose of multilevel linear analysis?

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