Factor AnalysisFactor Analysis is part of:
Easy and user-friendly
Easy and user-friendly XLSTAT is flawlessly integrated with Microsoft Excel which is the most popular spreadsheet worldwide. This integration makes it one of the simplest available tools to work with as it utilizes the same philosophy as Microsoft Excel. The program is accessible in a dedicated XLSTAT tab. The analyses are grouped into functional menus. The dialog boxes are user-friendly and setting up an analysis is straightforward.
Data and results shared seamlessly
Data and results shared seamlessly One of the greatest advantages of XLSTAT is the way you can share data and results seamlessly. As the results are stored in Microsoft Excel, anyone can access them. There is no need for the receiver to have an XLSTAT license or any additional viewer which makes your team-work easier and more affordable. In addition, results are easily integrable into other Microsoft Office software such as PowerPoint, so that you can create striking presentation in minutes.
Modular XLSTAT is a modular product. XLSTAT-Pro is a core statistical module of XLSTAT which includes all the mainstream functionalities in statistics and multivariate analysis. More advanced features contained in add-on modules can be added for specific applications. This way you can adapt the software to your needs making the software more cost-efficient.
Didactic The results of XLSTAT are organized by analysis and are easy to navigate. Moreover useful information is provided along with the results to assist you in your interpretation.
Affordable XLSTAT is a complete and modular analytical solution that can suit any analytical business needs. It is very reasonably priced so that the return of your investment is almost immediate. Any XLSTAT license comes with top level support and assistance.
Accessible - Available in many languages
Accessible - Available in many languages We have ensured XLSTAT is accessible to everyone by making the program available in many languages, including Chinese, English, French, German, Italian, Japanese, Polish, Portuguese and Spanish.
Automatable and customizable
Automatable and customizable Most of the statistical functions available in XLSTAT can be called directly from the Visual Basic window of Microsoft Excel. They can be modified and integrated to more code to fit to the specificity of your domain. Adding tables and plots as well as modifying existing outputs becomes easy. Furthermore, XLSTAT includes some special tools on the dialog boxes to generate automatically the VBA code in order to reproduce your analysis using the VBA editor or to simply load pre-set settings. This effortless automation of routine analysis will be a huge time saver on your part.
Principles of Factor Analysis
Exploratory factor analysis (or EFA) is a method which reveals the possible existence of underlying factors which give an overview of the information contained in a very large number of measured variables. The structure linking factors to variables is initially unknown and only the number of factors may be assumed.
Latent factors used in Factor Analysis
Three methods of extracting latent factors are offered by XLSTAT:
- Principle components: This method is also used in Principle Component Analysis (PCA).
- Principal factors: This method is probably the most used. It is an iterative method which enables the communalities to be gradually converged. The calculations are stopped when the maximum change in the communalities is below a given threshold or when a maximum number of iterations is reached. The initial communalities can be calculated according to various methods.
- Maximum likelihood: This method assumes that the input variables follow a normal distribution.
Rotation for Factor Analysis
Once the results have been obtained, they may be transformed in order to make them more easy to interpret, for example by trying to arrange that the coordinates of the variables on the factors are either high (in absolute value), or near to zero.
XLSTAT provides three types of rotations:
- Orthogonal rotations: Varimax, Quartimax, Equamax, Parsimax and Orthomax.
- Oblique transformations: Quartimin and Oblimin.
- Promax: A mixed procedure that consists initially of a Varimax rotation followed by an oblique rotation.
XLSTAT results for Factor Analysis
- Correlation/Covariance matrix: This table shows the data to be used afterwards in the calculations. The significant correlations are displayed in bold.
- Cronbach's Alpha
- Maximum change in communality at each iteration: This table is used to observe the maximum change in communality for the last 10 iterations. For the maximum likelihood method, the evolution of a criterion which is proportional to the opposite of the likelihood maximum is also displayed.
- Goodness of fit test: The goodness of fit test is only displayed when the likelihood maximum method has been chosen.
- Reproduced correlation matrix: This matrix is the product of the factor loadings matrix with its transpose.
- Residual correlation matrix: This matrix is calculated as the difference between the variables correlation matrix and the reproduced correlation matrix.
- Eigenvalues: This table shows the eigenvalues associated with the various factors together with the corresponding percentages and cumulative percentages.
- Factor pattern: This table shows the factor loadings (coordinates of variables in the vector space, also called factor pattern). The corresponding chart is displayed.
- Factor/Variable correlations: This table displays the correlations between factors and variables.
- Factor pattern coefficients: This table displays the coefficients of the factor pattern to be displayed. Multiplying the (standardized) coordinates of the observations in the initial space by these coefficients gives the coordinates of the observations in the factor space.
Where a rotation has been requested, the results of the rotation are displayed with the rotation matrix first applied to the factor loadings. This is followed by the modified variability percentages associated with each of the axes involved in the rotation. The coordinates of the variables and observations after rotation are displayed in the following tables - Factor structure. This table shows the correlations between factors and variables after rotation.
XLSTAT charts for Factor Analysis
- Variables charts: These plots display the variables in the new space. The initial variables can be represented in the form of vectors.
- Correlations charts: These plots show the correlations between the factors and initial variables. Here also the initial variables can be shown in the form of vectors.
- Observations charts: These charts represent the observations in the new space.