Factor analysis is a collection of methods used to examine how underlying constructs influence the responses on a number of measured variables.

There are basically two types of factor analysis: Exploratory and Confirmatory.

*Exploratory factor analysis (EFA)* attempts to discover the nature of the constructs influencing a set of responses.

*Confirmatory factor analysis (CFA)* tests whether a specified set of constructs is influencing responses in a predicted way.

__EFA__

The primary objectives of an EFA are to determine:

1. The number of common factors influencing a set of measures.

2. The strength of the relationship between each factor and each observed measure.

* *Some common uses of EFA are to:

· Identify the nature of the constructs underlying responses in a specific content area.

· Determine what sets of items “hang together" in a questionnaire.

· Demonstrate the dimensionality of a measurement scale. Researchers often wish to develop scales that respond to a single characteristic.

· Determine what features are most important when classifying a group of items.

· Generate “factor scores" representing values of the underlying constructs for use in other analyses.

__Steps to perform EFA__

There are seven basic steps to performing an EFA:

1. Collect measurements

2. Obtain the correlation matrix

3. Select the number of factors for inclusion

4. Extract your initial set of factors

5. Rotate your factors to a final solution

6. Interpret your factor structure

7. Construct factor scores for further analysis

__CFA__

The primary objective of a CFA is to determine the ability of a predefined factor model to fit an observed set of data.

Some common uses of CFA are to:

· Establish the validity of a single factor model.

· Compare the ability of two different models to account for the same set of data.

· Test the significance of a specific factor loading.

· Test the relationship between two or more factor loadings.

· Test whether a set of factors are correlated or uncorrelated.

· Assess the convergent and discriminant validity of a set of measures.

__Steps to perform CFA__

There are six basic steps to performing a CFA:

1. Define the factor model

2. Collect measurement

3. Obtain the correlation matrix

4. Fit the model to the data

5. Evaluate model adequacy

6. Compare with other models

Source: www.stat-help.com/**factor**.**pdf**

POsted by: Yogesh Raisinghani

**Operations _ Group 2**

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