SPSS Data Analysis

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Questions and Answers

What is the Mahalanobis distance an extension of?

Univariate distance from mean (correct)

Univariate distance from median

Bivariate distance from mean

Multivariate distance from median

What does the Mahalanobis distance give?

Distance from centroid in multivariate space for all predictors (correct)

Distance from mean in univariate space

Distance from median in multivariate space

Distance from centroid in multivariate space for one predictor

What is the purpose of checking the Mahalanobis distance against cut-offs based on the Chi square distribution?

To determine if an observation is very influential and may be problematic (correct)

To identify high leverage outliers

To identify multivariate outliers with low distances

To identify low influence outliers

What type of outliers have high leverage but low influence?

High leverage, low influence outliers Signup and view all the answers

What is the assumption being tested by detecting multivariate outliers?

No overly influential observations Signup and view all the answers

What question should be asked when dealing with outliers?

Are the outliers real? Signup and view all the answers

What can be done to reduce the intercorrelation of main effects with their interaction terms in a model?

Centre or standardize independent variables Signup and view all the answers

What is the primary goal of the weekly workshop/Q&A session?

To go beyond a surface level understanding of the lecture material Signup and view all the answers

When can you not worry about multicollinearity in a model?

When you're mainly interested in the overall model and have a large sample size Signup and view all the answers

Why is it important to know about the assumptions underlying statistical tests?

To use informed judgement about how problematic various violations are Signup and view all the answers

What is a common issue with statistics students?

Having good knowledge of relevant terms and analyses but lacking deeper understanding Signup and view all the answers

What is the purpose of working through difficult quiz questions in the workshop/Q&A session?

To identify and correct misunderstandings and clarify tricky concepts Signup and view all the answers

Which assumption is perhaps the most important to be careful of in regression-based analyses?

Independence of observations Signup and view all the answers

What is the main goal of Exploratory Factor Analysis (EFA)?

To identify the underlying factors in a set of variables Signup and view all the answers

What is the focus of the one 2-hour tutorial per week?

Practical details involved in conducting analysis in SPSS Signup and view all the answers

What is the purpose of the tutorial allocation system?

To allow students to select a tutorial time Signup and view all the answers

What should be done before conducting an Exploratory Factor Analysis (EFA)?

Prepare the data by checking for missing values and outliers Signup and view all the answers

What is the benefit of attending the workshop/Q&A session?

To gain a deeper understanding of the lecture material Signup and view all the answers

What is the main problem with using researcher degrees of freedom to p-hack?

It can lead to inaccurate results Signup and view all the answers

What should be done when dealing with assumptions in statistical tests?

Use informed judgement about how problematic various violations are Signup and view all the answers

What is the prerequisite for this course?

PSYC3010 Signup and view all the answers

What is the format of the lecture material?

One recorded lecture per week Signup and view all the answers

What is the primary goal of adjusting factor loadings in the model?

To maximize the similarity between the predicted and empirical variance-covariance matrices Signup and view all the answers

What constrains the values that can be predicted by the model?

The hypothesized factor structure Signup and view all the answers

What is generated by the pattern of factor loadings?

Predictions about the values of items in the predicted variance-covariance matrix Signup and view all the answers

What is the relationship between the predicted and empirical variance-covariance matrices?

The predicted matrix is similar to the empirical matrix Signup and view all the answers

What is the impact of the simplifying assumptions made by the model on our description of the data?

It compromises the description Signup and view all the answers

What is the purpose of estimating model parameters?

To generate predictions about the values of items in the predicted variance-covariance matrix Signup and view all the answers

What is the primary goal of Confirmatory Factor Analysis?

To identify the underlying factor structure of the data Signup and view all the answers

What does the factor structure in Confirmatory Factor Analysis represent?

The underlying patterns of the data Signup and view all the answers

What is the role of the V(E) variable in the model?

It represents the variance of the observed variable E Signup and view all the answers

What is the purpose of the C(E,O) variable in the model?

To estimate the covariance between E and O Signup and view all the answers

What does the Confirmatory Factor Analysis model evaluate?

The fit of the hypothesized model to the data Signup and view all the answers

What is the goal of evaluating the model's ability to recover the data?

To evaluate the fit of the hypothesized model to the data Signup and view all the answers

What is the relationship between the variables E, O, So, W, T, and Sy in the model?

They are all observed variables Signup and view all the answers

What is the purpose of the C(E,W) variable in the model?

To estimate the covariance between E and W Signup and view all the answers

Study Notes

Course Structure

The course consists of one recorded lecture per week, available beforehand, covering theory, examples, and applications.
Weekly workshop/Q&A sessions focus on clarifying and deepening understanding of the lecture material.
One 2-hour tutorial per week covers practical details involved in conducting analysis in SPSS.

Assumption: No Overly Influential Observations

Detecting multivariate outliers using Mahalanobis distance, a multivariate extension of univariate distance from mean.
Check against cut-offs based on Chi square distribution (p < 1: very influential, may be problematic).
High leverage, low influence outliers can be problematic.
Ways to address multivariate outliers:
- Go back and look if any variables can be combined (or deleted).
- Factor analyze the set of independent variables.
- Centre or standardize independent variables.
- Collect more data to increase precision of betas.

Assumptions Testing

Importance of knowing assumptions underlying statistical tests.
Real-life data rarely conform precisely to assumptions, so informed judgement is needed about how problematic violations are.
Regression-based analyses are generally robust to distributional assumptions.
Independence of observations is crucial to be careful of.
Being knowledgeable about assumptions helps navigate decisions.
Transparency is key: don't use researcher degrees of freedom to p-hack.

Exploratory Factor Analysis (EFA)

Conceptual introduction to EFA: aims of the analysis and research questions.
How EFA works: preparing to conduct an EFA, determining how many factors to retain.
Evaluating the model: how accurately can the model recover the data?

Confirmatory Factor Analysis (CFA)

How CFA works: evaluating how well the hypothesized factor structure accounts for data.
Model parameters estimation: pattern of factor loadings generates predictions about the values of items in the predicted variance-covariance matrix.
Adjusting factor loadings to maximize similarity between predicted and empirical values.
Hypothesized factor structure constrains values that can be predicted by the model.

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Description

This course covers the theory and practical applications of data analysis using SPSS. It includes lectures, workshops, and tutorials to help students understand and conduct analysis in SPSS.