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Data Analysis Techniques Discussion

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Running Head: DATA ANALYSIS TECHNIQUES 1
Data Analysis Techniques
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DATA ANALYSIS TECHNIQUES 2
Data Analysis Techniques
A structural equation model (SEM) is a statistical analysis technique for analyzing
structural relationships, a combination of pathway analysis and confirmatory factor analysis. A
SEM is used to address interdependent relationships among variables simultaneously so that
covariates in mechanistic pathways are elucidated, not dropped. They also help estimate the
multiple and interrelated dependence in a single analysis. Every SEM follows the same series of
steps. First, specify a model (i.e., diagram, equation (“What is Structural Equation Modeling? “,
n.d.).
Advantages of SEM
The first advantage is validity. Structural equation modeling helps a researcher acquire a
more valid conclusion by allowing the use of an indicator variable in every construct. Typically,
theories always refer to variables that aren’t directly and can be inferred from indicator variables.
This is where SEM comes in operationalizing the constructs (Werner, 2009).
Second is measurement error or reliability. Structural equation modeling takes advantage
of the fact that data from social sciences contains a sizeable measurement error. It includes
variables with this error that is similar to the one in observed variables. It ensures that constructs
relationships are not affected by the error.
Next is the complex model. This analysis technique enables test and model complex
relationship patterns, which includes hypotheses in general. In other analysis techniques, it may
require a researcher to use separate analyses.
Finally, there is a confirmatory approach. Most statistical procedures in testing hypotheses
are usually based on the explanation of variance in single variables. This may not work in the

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Running Head: DATA ANALYSIS TECHNIQUES Data Analysis Techniques Author’s Name Institutional Affiliation 1 DATA ANALYSIS TECHNIQUES 2 Data Analysis Techniques A structural equation model (SEM) is a statistical analysis technique for analyzing structural relationships, a combination of pathway analysis and confirmatory factor analysis. A SEM is used to address interdependent relationships among variables simultaneously so that covariates in mechanistic pathways are elucidated, not dropped. They also help estimate the multiple and interrelated dependence in a single analysis. Every SEM follows the same series of steps. First, specify a model (i.e., diagram, equation (“What is Structural Equation Modeling? “, n.d.). Advantages of SEM The first advantage is validity. Structural equation modeling helps a researcher acquire a more valid conclusion by allowing the use of an indicator variable in every construct. Typically, theories always refer to variables that aren’t directly and can be inferred from indicator variables. This is where SEM comes in operationalizing the constructs (Werner, 2009). Second is measurement error or reliability. Structural equation modeling takes a ...
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