Multidisciplinary Research Lab

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Quantitative Data Analysis Workshop Series

Structural Equation Modelling Made Easy - Part 1 Cost: GHS 500 Two Sessions: Book Only One - 8 & 9 Nov and 15 & 16 Nov 2018To Participate or Make Enquiries, Call: 055 986 8938

Structural Equation Modelling Made Easy – Part 1

Structural Equation Modelling (SEM) is a multivariate data analysis technique that combines factor analysis and multiple regression analysis in testing networks of causal relationships between variables. The course is aimed at social science researchers and research students which have some working knowledge of regression and factor analysis techniques and would like to extend their knowledge into analyzing more complex models. The session will be very practical with hands-on training using SPSS and Amos.

Topics to be covered include:

  1. Introduction to Structural Equation Modelling (SEM)
  2. Confirmatory Factor Analysis
  3. Model Fit and Model Modification
  4. Validating the Measurement Model
  5. Specifying the Structural Model
  6. Building Nested Models

Who should attend?

Students and researchers who need to develop quantitative skills for research

  • Dates: Two Sessions Available, Book Only One Session
  • Session A: 8 – 9 Nov. 2018    Session B: 15 – 16 Nov. 2018
  • Only 10 slots Available per Session. Call to Book a Slot

Cost and Venue

  • Cost:  GHS 500     Venue: PRF Research Lab, North Legon

Enquiries and Bookings

  • To Participate or Make Enquiries, Call: 055 986 8938
  • Send questions to – Dr. Sheena Lovia Boateng [ lovia @ pearlrichards .org]

Computing

  • Because this is a hands-on course, you will need to bring your own laptop loaded with a recent version of SPSS (version 20 or later) and AMOS. Power outlets will be available at each seat.

Simple Linear, Multiple and Hierarchical Regression

This workshop will teach participants techniques in how to test the significance of relationships between dependent and independent variables. They will obtain skills in testing causal relationships, as well as how to find support for research hypotheses formulated for specific studies.

Learning Outcomes

By the end of the workshop, participants will know:

  • The components of the regression equation/ model.
  • How to construct a regression equation/ model.
  • How to run simple, multiple and hierarchical regression analysis.
  • How to interpret and present the SPSS output.

Read Workshop Report

Descriptive Statistics and Exploratory Factor Analysis (with Pearson Correlation)

This workshop will teach participants techniques in how to summarise categorical and continuous data, understand the structure of a large set of variables and how to reduce them to more a manageable size, as well as to determine the strength and direction of the relationships between these variables.

Learning Outcomes

By the end of the workshop, participants will know:

  • When to use Descriptive statistics, EFA and Pearson correlation
  • How to run Descriptive statistics, EFA and Pearson correlation in SPSS
  • How to interpret and present the SPSS output

Read Workshop Report

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