Question 1

Still using the same example, which of the following statements is correct? (You may select more than one option.)
A) Athletes are nested within coaches.
B) Coaches are nested within athletes.
C) Clubs are nested with countries.
D) Countries are nested within coaches.

Accepted Answer

Athletes are typically grouped under coaches, meaning they are nested within coaches. Similarly, clubs are often part of larger national organizations, meaning clubs are nested within countries.

Question 2

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?
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.

Accepted Answer

Applying a covariance structure that is too simple increases the likelihood of making a Type I error, which is rejecting the null hypothesis when it is actually true. This is because the model estimates may not fully capture the variability in the data, leading to incorrect conclusions. Therefore, it is important to carefully consider the appropriate covariance structure for the data being analyzed.

Question 3

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

Accepted Answer

In this scenario, both the intercept and slope could vary due to individual differences in parental influence and coach's qualifications, suggesting a random intercept and random slope model.

Question 4

Prior to conducting a multilevel analysis, how might you check linearity and any unusual cases (e.g. outlying cases)?
A) Scatterplots
B) Bar charts
C) Pie charts
D) Radar plot

Accepted Answer

Scatterplots are the best choice for checking linearity and identifying any unusual cases or outliers. They allow for visual inspection of the relationship between variables and can easily identify any patterns or deviations from linearity. Bar charts, pie charts, and radar plots are not appropriate for evaluating the linearity of data or identifying outliers.

Question 5

Which of the following would not be expected to change with time?
A) Attitude towards training
B) Gender of participants
C) Anxiety prior to competition
D) Cellular mitochondria density during aerobic training

Accepted Answer

Gender is a static characteristic and does not change over time. Attitude towards training, anxiety, and cellular mitochondria density are all factors that can change over time with experience and training.

Question 6

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?
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.

Accepted Answer

Dependency between contextualized variables means that there is a correlation between the residuals within the model. This violates the assumption of independence of residuals, which can lead to biased parameter estimates and incorrect statistical inferences.

Question 7

Which of the following descriptions best applies to this graph? 
A) Fixed intercept, random slope
B) Fixed intercept, fixed slope
C) Random intercept, random slope
D) Random intercept, fixed slope

Accepted Answer

The answer of Which of the following descriptions best applies...

Question 8

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?
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.

Accepted Answer

A chi-square value of 7.05 at one degree of freedom is significant at the .01 level.

Question 9

Which of the following is not a form of polynomial curve?
A) Linear
B) Quadratic
C) Cubic
D) Binomial

Accepted Answer

Binomial is not a form of polynomial curve. A polynomial is an expression consisting of variables and coefficients that involves only the operations of addition, subtraction, multiplication, and non-negative integer exponents. Binomial, on the other hand, refers to an algebraic expression containing two terms.

Question 10

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

Accepted Answer

Group mean centring involves subtracting the group mean from an individual score to reduce multicollinearity.

Question 11

Which of the following are alternative names for multilevel linear analysis? (You may select more than one option.)
A) Random coefficient model
B) Linear mixed model
C) Hierarchical linear model
D) Dependent variable model

Accepted Answer

B AND C

Question 12

What is the purpose of multilevel linear analysis?
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.

Accepted Answer

Multilevel linear analysis is used to analyse data with a hierarchial structure, such as data collected from individuals nested within groups. It allows for the examination of both within-group and between-group effects, providing a more comprehensive understanding of the data.

Question 13

Which of the following descriptions best applies to this graph? 
A) Fixed intercept, random slope
B) Fixed intercept, fixed slope
C) Random intercept, random slope
D) Random intercept, fixed slope

Accepted Answer

The answer of Which of the following descriptions best applies...

Question 14

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

Accepted Answer

The growth model is a means of examining rate of development or change in a given variable. It is commonly used in research to analyze changes in a particular construct over a period of time. In this case, the growth model would be an appropriate choice to examine the development of player confidence when exposed to structured coaching sessions.

Question 15

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?
A) Hurvich and Tsai's criterion (AICC)
B) Akaike's information criterion (AIC)
C) Bozdogan's criterion (CAIC)
D) Schwarz's Bayesian criterion (BIC)

Accepted Answer

AICC is designed specifically for small sample sizes and accounts for the number of predictor variables in the model. It is preferred over the other criteria when dealing with small sample sizes.

Question 16

Where would you position the club (i.e. what level) in the model of Q3?
A) 3
B) 4
C) 5
D) 6

Accepted Answer

The club is a social organization that provides its members with a variety of activities and services. It is not a business or a government agency, so it would not be positioned at level 6. It is also not a family or a school, so it would not be positioned at level 3. It is more like a community organization or a religious organization, so it would be positioned at level 4 or 5.

Question 17

What is the minimum number of levels required to perform a multilevel linear analysis?
A) 2
B) 3
C) 4
D) 5

Accepted Answer

A minimum of two levels are required for a multilevel linear analysis. The first level is typically the individual level, and the second level is the grouping variable, such as classroom or school. Additional levels may be included if necessary, but two levels are the minimum.

Question 18

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

Accepted Answer

If a lack of linearity is identified as an issue, one option is to transform the data. This may involve applying logarithmic or square root transformations to the variables in order to improve linearity.

Question 19

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

Accepted Answer

There are four levels involved in this analysis:
1. Confidence levels of athletes
2. Athletics club (to which the athlete belongs)
3. Coaches (of the athlete)
4. Country (where the athletics club is located).
Therefore, choice B (4) is the correct answer.

Question 20

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

Accepted Answer

Fixed effects are effects that are constant across all levels of the coaching pyramid. In this case, the effects of the coaching pyramid would be the same for all coaches, regardless of their level of experience or the team they are coaching.

Quiz 21: Multilevel Linear Models

Still using the same example, which of the following statements is correct? (You may select more than one option.)

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?

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?

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

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

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?

Which of the following descriptions best applies to this graph?

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?

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

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

Which of the following are alternative names for multilevel linear analysis? (You may select more than one option.)

What is the purpose of multilevel linear analysis?

Which of the following descriptions best applies to this graph?

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) ?

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

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

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

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?

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?