Transcript WritingtheResultsSec..

Writing the Results Section
Some Studies with Results Sections Reporting
Common Statistical Tests and Procedures
 Study which reports the results of chisquare tests of hypotheses
 Study which reports the results of factor
analysis, logistic regression, and multiple
regression analysis
 Study which reports the results of ANOVA
tests of main and interaction effects in an
experiment
 Study which reports the results of ANOVA
tests in a non-experimental design
Sample Results reporting from Some of our
Previous Analyses, Labs, and Exam
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Reporting an ANOVA result for a one-way ANOVA
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To test the hypothesis that marital status has a significant impact on
hours spent watching TV, a one-way analysis of variance was
conducted. A significant value of F (4, 1483) of 10.684 was obtained
(p<.001). The effect size (partial eta squared) was .028. Power to
detect the effect was .999. The Levene test for the equality of
variances among the levels of the independent variable (marital
status) found that the variances were significantly different (F =
4.622, p < .01), suggesting that an alternative post hoc test for pairwise differences of means should be used. The mean TV hours
watched by marital status were: widowed, 3.91; separated, 3.00;
divorced, 2.96, never married, 2.91; and married, 2.67. Post-hoc
tests of pair-wise mean differences using the Tamhane T2 statistic
indicated that significant differences in hours spent watching television
were obtained between married and widowed, between widowed and
divorced, and between widowed and never married. Although the
significant overall F and significant post hoc differences indicated that
there was a tendency for marital status to influence number of hours
spent watching TV, the effect size was very small even given statistical
power of .99.
Sample Results reporting from Some of our
Previous Analyses, Labs, and Exam, cont’d
 Reporting the results of a t-test:
 The hypothesis was tested that people who own
their own home watch significantly fewer hours
of TV per day than people who do not own their
own home (t (unequal variances) = -3.914, df =
529.171, p <.005). People who owned their
own home watched an average of 2.70 hours of
TV per day, while people who did not own their
own home watched an average of 3.37 hours of
TV per day.
Writing up a Multiple Regression
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Reporting the results of a hierarchical multiple regression analysis
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To test the hypothesis that a country’s level of male literacy is a
function of three variables, the country’s annual increase in population,
percentage of people living in cities, and gross domestic product, a
hierarchichal multiple regression analysis was performed. Tests for
multicollinearity indicated that a very low level of multicollinearity was
present (VIF = 1.54 for people living in cities, 1.15 for annual
increase in population, and 1.663 for gross domestic product). People
living in cities was the first variable entered, followed by annual
population increase and then GDP, according to our theory. Results of
the regression analysis provided partial confirmation for the research
hypothesis. Beta coefficients for the three predictors were people living
in cities, β = .493, t = 5.539, p < .001; annual population increase, β
= -.517, t = -6.698, p < .001; and gross domestic product, β = -.063,
t = -.676, p = .501, n.s. The best fitting model for predicting rate of
male literacy is a linear combination of the country’s annual population
increase and the percentage of people living in cities (R = .762, R2 =
.581, F (2,82) = 56.823, p < .001). Addition of the GDS variable did
not significantly improve prediction (R2 change = .002. F = .457, p =
.501).
Where to Look for Guidance in the
APA Manual
 For the best guidance on writing the results section,
consult the APA style manual, pp. 20-27, and the
section on tables and figures, pp. 147-204, which
includes many examples for different types of
analyses
 On pages 140-144 there are tables about how to refer
to statistical symbols and abbreviations in the text
 Generally speaking, when preparing your paper for
publication you italicize these:
 N, M, df, p, SS, SE t, F, a, and b, R, R2, H when
referring to a hypothesis
 And you leave these in regular type:
 MANOVA, ANOVA, β, µ, or other Greek symbols, and
superscripts and subscripts that don’t refer to variables
such as when you’re squaring or indicating that X is the
first variable, second variable, etc
General APA Guidelines on Writing
the Results Section
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Your main priority in the Results section is to report on the
tests of your hypothesis and tell your reader whether or not
you obtained evidence in support of your research
hypotheses, or failed to do so
Tie your writing closely to the hypotheses. Restate the
hypothesis under discussion near the beginning of the
paragraph and identify the type of test used to assess it.
Discuss all the hypotheses in the order in which you presented
them
If there is a great deal of material, for example multiple
dependent variables for which you want to report means, use
a table instead of text. Text is for the statistic used to test
the hypothesis, the df, the p level, power, effect size, etc or
for a report of means if there are only a few variables
Don’t report raw scores even in a table, although you may
refer the reader to where they can find it if they are
interested and there are no human subjects issues involved in
making it available
More Guidelines from APA
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Generally tables are preferred to figures, and no figures are
preferred to figures that are home-made looking or not
camera ready
Most publishers are not interested in reproducing
photographs and will complain about it unless they are
required for understanding (for example, they constitute
the levels of one of the factors in an ANOVA design)
Be sure to refer to all tables and figures in the text; don’t
just stick them in without warning
The usual convention is to leave space for a table and fill
that space with a note to the publisher that says [Table 1
about here] in the spot where you want it to go. Then you
put the tables in order at the end of the document after the
references and appendices
Whenever possible include the items used in your surveys
or questionnaires in an appendix which you mention in the
text of the Results section
More Guidelines from APA
 What to report:
 One of the first things you report is the reliability of
any measures you have used. Report alpha reliability
or repeated measures correlations. If your alpha falls
below .80 for any measure you should rethink using it
 Generally you should report the test statistic, the df,
the probability level, the power, the effect size, the
means if there are not too many, whether or not the
hypothesis was supported, the direction of any effects
or mean differences. Ns, means and standard
deviations can be reported in a table. Some journals
encourage reporting of confidence intervals
And More APA Guidelines
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In a factorial design where there are multiple cells, also
report the cell means, sample sizes for the cell, and cell
standard deviations
For an F test, reproduce the ANOVA table in a separate
table (showing the SS for between and within, the mean
squares, F, etc. This would include not only experiments or
factorial designs but also other kinds of statistics whose
significance is tested by F such as R2
Some journals require you to provide the variancecovariance or correlation matrix when you report on a
multiple regression or correlation analysis. You can get this
output easily from SPSS if needed
Consult the APA manual for further details on specific
analyses
Consult the Results section of papers from your list of
references and see what they reported
What Doesn’t Go in the Results
Section
 Remember that the Results section is not the place to
speculate about why you got the results you did (you
will do that in the Discussion), nor is it the place to
say why you studied what you did (you should have
done that in the Literature Review/Rationale) or to say
how you did things (you should have done that in the
Method section)
 Just tell the reader what you found
 Try to avoid saying things like, “even though the
results were not significant, men did X more than
women”. If it wasn’t a significant result, best to not
report or interpret it (although some papers are full of
results that “just missed significance”)