Related Experiment Video
Updated: Aug 15, 2025

08:27
Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
Published on: September 27, 2019
7.0K
FINDOUT: Using Either SPSS Commands or Graphical User Interface to Identify Influential Cases in Structural Equation
Shu Fai Cheung1, Ivan Jacob Agaloos Pesigan1
1Department of Psychology, University of Macau.
Multivariate Behavioral Research
|January 5, 2023
Summary
Researchers can now identify influential cases in AMOS software using the new FINDOUT toolset. This helps ensure the reliability of structural equation modeling (SEM) results.
Area of Science:
- Statistics
- Psychometrics
- Social Sciences
Background:
- Structural Equation Modeling (SEM) is widely used in various research fields.
- SEM results can be sensitive to influential cases, impacting findings' reliability.
- Existing tools for identifying influential cases are primarily available for R, not AMOS.
Purpose of the Study:
- To introduce the FINDOUT toolset for identifying influential cases in AMOS.
- To provide methods for examining the impact of influential cases on SEM results.
- To enhance the robustness checks available for AMOS users.
Main Methods:
- Development of the FINDOUT toolset, comprising SPSS extension commands and an AMOS plugin.
- SPSS commands can be executed via syntax or custom dialogs.
- The AMOS plugin is accessible through the AMOS software menu.
Main Results:
- The FINDOUT toolset enables the identification of influential cases within AMOS analyses.
- Researchers can utilize the toolset to assess how specific observations affect SEM outcomes.
- The tools offer a practical solution for AMOS users to investigate result sensitivity.
Conclusions:
- The FINDOUT toolset addresses a gap in available diagnostic tools for AMOS users.
- These tools empower researchers to better evaluate the robustness of their SEM findings.
- Adoption of FINDOUT can lead to more reliable and trustworthy research conclusions in SEM.
More Related Videos
Related Concept Videos
Statistical Package for the Social Sciences (SPSS)
461
The Statistical Package for the Social Sciences, or SPSS, is a data management and analysis software suite. Developed by SPSS Inc. in 1968 and acquired by IBM in 2009, this tool was initially designed for social science data analysis, evolving to serve a wider range of disciplines. It was later renamed to Statistical Product and Service Solutions.
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
461
Statistical Analysis: Overview
6.8K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
6.8K
Statistical Analysis System (SAS)
281
SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
281
Statistical Software for Data Analysis and Clinical Trials
715
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
715
Econometric Views (EViews)
204
Econometric Views, often stylized as EViews, is a package that merges statistical analysis with econometric studies. It is designed to provide tools for time series analysis, forecasting, and econometric model simulation. The software originated from MicroTSP software and has evolved significantly since its inception in 1981. The history of EViews is marked by a continuous effort to enhance its computational speed and user interface. It was initially developed for large computing systems but...
204
Outliers and Influential Points
4.2K
An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500), while others may indicate that something unusual is happening. Outliers are present far from the least squares line in the vertical direction. They have large "errors," where the "error" or residual is the...
4.2K

