datatotext: a consumer-oriented approach to data analysis

DataToText: A Consumer-Oriented

Approach to Data Analysis

David A. Kenny David A. Kenny

University of ConnecticutUniversity of Connecticut http://davidakenny.net/doc/aps10.ppt

http://davidakenny.net/doc/aps10.doc

Data Analysis for Methodologists

Begin with a hypothesis that is embedded within a statistical model.

Develop a research and measurement design to estimate the parameters of that model.

Gather data; test model assumptions; and estimate the model’s parameters.

Choose the best model.

Data Analysis for Practitioners

What do I have to click in SPSS?

What from my SPSS output do I put where in my results section?

Consumer versus “Industry” Perspective

For data analysis, quantitative psychologists are the “industry” or at least part of the industry.

The spirit of DataToText is an attempt to get us to become more “consumer-oriented.”

DataToText Project Have the researcher tell DataToText

what is the research question.

DataToText performs the requisite analyses.

DataToText gives the results from those analyses:

computer output

a written description

Example 1http://davidakenny.net/moderate.htm

Moderation Analysis

Livi et al.: The effect of Noise Sensitivity (X) on Stress (Y) is moderated by the Need for Cognitive Closure (M)

Moderation Example

SyntaxGives results in words,

tables, and picturesTests assumptionsGives warningsSpecialized output

How Positively the Wife Sees the Husband

Wife Satisfaction

Example 2

Husband Satisfaction

Actor Wife

Actor Husband

Partner HusbandPartn

er

Wife

How Positively the Wife Sees the

Husband

http://davidakenny.net/ddt/apimd.htm

Syntax Picture

Specialized Output

Advantages and Disadvantages

DataToText is Mindless!

Thought and intelligence is needed for:

What analysis to do

The execution of the analysis

The interpretation of the analysis

High school student Jenna Smith randomly throwing variables into the macro.

Researcher Brad Anderson not knowing anything about

testing moderation.

Definitely bad, probably terrible.

However, it might be better than what would have otherwise been done.

AdditionallySometimes warnings may alert the user

that the wrong analysis was done.

For example, both macros provide a warning if a dichotomous variable is analyzed.

DataToText is Mindless!

about:

What analysis to do

The execution of the analysis

The interpretation of the analysis

Data Analysis Requires Thought

Not all problems have a flow-chart structure

CFA

ARIMA modeling

However

Some problems have a flow-chart structure (though we might disagree some about that flow-chart).

For many analyses we do have explicit or implicit standards for reporting of results.

Also Keeps everything straight. Avoids errors.

DataToText while it may typically fail to perform the best analysis, it might often create a better analysis than that done by even a skilled data analyst.

Provides warnings.

Makes assumptions explicit and can provide statistical tests of some of them.

Warnings

DataToText issues warnings:

A dichotomous outcome variable

Outliers

Colinearity

Low Power

Assumption Testing Is Like Flossing

Something we know that we should do but do not do as often we should.

DataToText can test certain assumptions

level of measurement

distributional

outliers

DataToText is Mindless!

about:

What analysis to do

The execution of the analysis

The interpretation of the analysis

The Researcher Needs to

Understand the Results Good data analysis is more than doing

the right analysis; the researcher must still understand the meaning of the results.

However Because DataToText provides a verbal

summary of the results, some researchers might better understand their results by using the approach.

Moreover Output produced by DataToText may be

more intelligible to the reader and so although the data analyst may not understand the results, the reader may be able to!

Packages vs. Open Source

Packages

PASW (née SPSS), SAS

Accessible but costly

Updates sometimes without backwards compatibility

Open Source: R

Feedback

Please let me know what you think.

david.kenny@uconn.edu

http://davidakenny.net/doc/aps10.ppt

http://davidakenny.net/doc/aps10.doc

Special Thanks to My Lab• Thomas Ledermann• Amanda Snook• Randi Garcia