Steps to Address Missing Data
Steps to Address Missing Data Addressing missing data is an important step in the data preprocessing phase of any data analysis or machine learning project. Here are some common strategies for handling missing data: Identify Missing Data: Begin by identifying which features have missing values and the extent of the missing data. Understanding the pattern […]
How to Address Missing Data in SPSS
Missing Data Using SPSS If you are missing much of your data, this can cause several problems. The most apparent problem is that there simply won’t be enough data points to run your analyses. The EFA, CFA, and path models require a certain number of data points in order to compute estimates. This number increases […]
Cronbach’s Alpha Reliability Analysis in SPSS – Results Interpratation
In this tutorial, we discuss how to conduct Cronbach’s Alpha Reliability Analysis in SPSS and Results Interpratation. The Tutorial is presneted in the folowing Youtube video, prepared by Our Team. m
Conducting Frequencies Descriptive Statistics using SPSS – and Results Interpratation
In this section, we discuss how to Conduct Frequencies Descriptive Statistics using SPSS – and Results Interpratation. The video below is a step by step guidance on how to Conduct Frequencies Descriptive Statistics using SPSS – and Results Interpratation.
Before starting this exercise, read Chapter 3 in Big Hair on EFA, and Chapter 15 in Little Hair starting on page 425.
Exercise #1 – Fall Semester 2023 Before starting this exercise, read Chapter 3 in Big Hair on EFA, and Chapter 15 in Little Hair starting on page 425. Execute Exploratory Factor Analysis (EFA) using the Samouel’s Customer Data. For this analysis, you will use all 200 respondents. Do not split the sample to execute EFA. […]
Execute Exploratory Factor Analysis (EFA) using the Samouel’s Customer Data
Exercise #1 – Fall Semester 2023 Before starting this exercise, read Chapter 3 in Big Hair on EFA, and Chapter 15 in Little Hair starting on page 425. Execute Exploratory Factor Analysis (EFA) using the Samouel’s Customer Data. For this analysis, you will use all 200 respondents. Do not split the sample to execute EFA. […]
Missing Value Analysis (MVA) using SPSS
Missing Value Analysis (MVA) Missing value or data is the absence of a datapoint in a dataset. The problem of missing value occurs when a respondent fails to answer a question or a data entry problem on the part of the researcher or errors in the data collection process. Endeavour to always conduct a missing […]
Factor loading and Cross-loading using SPSS
Factor loading and Cross-loading Because constructs are measured indirectly, it is recommended that you have at least three items/indicators/questions measuring each of them. For example, in the data used for this post, university faculty members were asked about their perceived quality of information in Wikipedia using the following five different questions. QU1: Articles in Wikipedia are reliable […]
Discriminant Validity using SPSS
Discriminant Validity using SPSS Your main reason for conducting discriminant validity for your study will be to show how distinct an item or set of items is from others. In other words, you are interested in showing that items measuring different constructs or variables have poor relationships or low correlation exist between them. If you […]
Discriminant Validity through Fronell-Larcker Criterion SPSS
Discriminant Validity through Fronell-Larcker Criterion The Fronell-Larcker criterion is one of the most popular techniques used to check the discriminant validity of measurements models. According to this criterion, the square root of the average variance extracted by a construct must be greater than the correlation between the construct and any other construct. Once this condition […]
