Podcast
Questions and Answers
What is the Mahalanobis distance an extension of?
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?
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?
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?
What type of outliers have high leverage but low influence?
What is the assumption being tested by detecting multivariate outliers?
What is the assumption being tested by detecting multivariate outliers?
What question should be asked when dealing with outliers?
What question should be asked when dealing with outliers?
What can be done to reduce the intercorrelation of main effects with their interaction terms in a model?
What can be done to reduce the intercorrelation of main effects with their interaction terms in a model?
What is the primary goal of the weekly workshop/Q&A session?
What is the primary goal of the weekly workshop/Q&A session?
When can you not worry about multicollinearity in a model?
When can you not worry about multicollinearity in a model?
Why is it important to know about the assumptions underlying statistical tests?
Why is it important to know about the assumptions underlying statistical tests?
What is a common issue with statistics students?
What is a common issue with statistics students?
What is the purpose of working through difficult quiz questions in the workshop/Q&A session?
What is the purpose of working through difficult quiz questions in the workshop/Q&A session?
Which assumption is perhaps the most important to be careful of in regression-based analyses?
Which assumption is perhaps the most important to be careful of in regression-based analyses?
What is the main goal of Exploratory Factor Analysis (EFA)?
What is the main goal of Exploratory Factor Analysis (EFA)?
What is the focus of the one 2-hour tutorial per week?
What is the focus of the one 2-hour tutorial per week?
What is the purpose of the tutorial allocation system?
What is the purpose of the tutorial allocation system?
What should be done before conducting an Exploratory Factor Analysis (EFA)?
What should be done before conducting an Exploratory Factor Analysis (EFA)?
What is the benefit of attending the workshop/Q&A session?
What is the benefit of attending the workshop/Q&A session?
What is the main problem with using researcher degrees of freedom to p-hack?
What is the main problem with using researcher degrees of freedom to p-hack?
What should be done when dealing with assumptions in statistical tests?
What should be done when dealing with assumptions in statistical tests?
What is the prerequisite for this course?
What is the prerequisite for this course?
What is the format of the lecture material?
What is the format of the lecture material?
What is the primary goal of adjusting factor loadings in the model?
What is the primary goal of adjusting factor loadings in the model?
What constrains the values that can be predicted by the model?
What constrains the values that can be predicted by the model?
What is generated by the pattern of factor loadings?
What is generated by the pattern of factor loadings?
What is the relationship between the predicted and empirical variance-covariance matrices?
What is the relationship between the predicted and empirical variance-covariance matrices?
What is the impact of the simplifying assumptions made by the model on our description of the data?
What is the impact of the simplifying assumptions made by the model on our description of the data?
What is the purpose of estimating model parameters?
What is the purpose of estimating model parameters?
What is the primary goal of Confirmatory Factor Analysis?
What is the primary goal of Confirmatory Factor Analysis?
What does the factor structure in Confirmatory Factor Analysis represent?
What does the factor structure in Confirmatory Factor Analysis represent?
What is the role of the V(E) variable in the model?
What is the role of the V(E) variable in the model?
What is the purpose of the C(E,O) variable in the model?
What is the purpose of the C(E,O) variable in the model?
What does the Confirmatory Factor Analysis model evaluate?
What does the Confirmatory Factor Analysis model evaluate?
What is the goal of evaluating the model's ability to recover the data?
What is the goal of evaluating the model's ability to recover the data?
What is the relationship between the variables E, O, So, W, T, and Sy in the model?
What is the relationship between the variables E, O, So, W, T, and Sy in the model?
What is the purpose of the C(E,W) variable in the model?
What is the purpose of the C(E,W) variable in the model?
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.
