Factor analysis is a powerful
data reduction technique that enables researchers to investigate concepts that cannot easily be measured directly
. By boiling down a large number of variables into a handful of comprehensible underlying factors, factor analysis results in easy-to-understand, actionable data.
What is the basic purpose of factor analysis explain the conditions that are required to be satisfied before carrying out a factor analysis exercise?
Factor analysis is a technique that
is used to reduce a large number of variables into fewer numbers of factors
. This technique extracts maximum common variance from all variables and puts them into a common score. As an index of all variables, we can use this score for further analysis.
What is factor analysis What is the basic purpose of factor analysis what assumptions should be fulfilled to use factor analysis?
The basic assumption of factor analysis is that
for a collection of observed variables there are a set of underlying variables called factors (smaller than the observed variables)
, that can explain the interrelationships among those variables.
What is the purpose of factor analysis psych?
Applications in psychology
Factor analysis is
used to identify “factors” that explain a variety of results on different tests
. For example, intelligence research found that people who get a high score on a test of verbal ability are also good on other tests that require verbal abilities.
What is the advantage of factor analysis?
The advantages of factor analysis are as follows:
Identification of groups of inter-related variables, to see how they are related to each other
. Factor analysis can be used to identify the hidden dimensions or constructs which may or may not be apparent from direct analysis.
How do you interpret a factor analysis in SPSS?
Initial Eigenvalues Total: Total variance. Initial Eigenvalues % of variance: The percent of variance attributable to each factor. Initial Eigenvalues Cumulative %: Cumulative variance of the factor when added to the previous factors. Extraction sums of Squared Loadings Total: Total variance after extraction.
What is path analysis used for?
Path analysis, a precursor to and subset of structural equation modeling, is
a method to discern and assess the effects of a set of variables acting on a specified outcome via multiple causal pathways
.
What are the two main forms of factor analysis?
There are two types of factor analyses,
exploratory and confirmatory
.
What is the next step after factor analysis?
The next step is
to select a rotation method
. After extracting the factors, SPSS can rotate the factors to better fit the data. The most commonly used method is varimax.
What type of data is needed for factor analysis?
Factor analysis is designed for
interval data
, although it can also be used for ordinal data (e.g. scores assigned to Likert scales). The variables used in factor analysis should be linearly related to each other. This can be checked by looking at scatterplots of pairs of variables.
What is factor analysis in psychology example?
For example, when you take a multiple choice Introductory Psychology test, a factor analysis can
be done to see what types of questions you did best on and worst on
(maybe they did best on factual types of questions but really poorly on conceptual types of questions).
What is uniqueness in factor analysis?
Uniqueness is
the variance that is ‘unique’ to the variable and not shared with other variables
. It is equal to 1 – communality (variance that is shared with other variables). For example, 61.57% of the variance in ‘ideol’ is not share with other variables in the overall factor model.
What are the disadvantages of factor approaches?
Disadvantages of Factor Analysis:
2.
Naming of the factors can be difficult multiple attributes can be highly correlated with no apparent reasons
. 3. If the observed variables are completely unrelated the factor analysis is unable to produce meaningful pattern.
Is factor analysis quantitative or qualitative?
Exploratory Factor analysis is a research tool that can be used to make sense of multiple variables which are thought to be related. This can be particularly useful when a qualitative methodology may be the more appropriate method for collecting data or measures, but
quantitative analysis
enables better reporting.
How do you interpret a factor analysis?
- Step 1: Determine the number of factors. If you do not know the number of factors to use, first perform the analysis using the principal components method of extraction, without specifying the number of factors. …
- Step 2: Interpret the factors. …
- Step 3: Check your data for problems.
Why do we do factor analysis in SPSS?
Factor analysis is a method of data reduction. It does this by
seeking underlying unobservable (latent) variables that are reflected in the observed variables (manifest variables)
. … Simple structure is pattern of results such that each variable loads highly onto one and only one factor.
