Outline: What is comparative statistics Deciding which statistical test to do Dependent and Independent variable

1. COMPARATIVE STATISTICS
in medical research 😉
Part 2 OF Course 2
TEAM 32 - TORASIF Research webinar
August 27th, 2022
FORTUNE EFFIONG
Director for Research, TORASIF

2. WHAT WILL BE COVERED IN THIS PART
INTRO TO COMPARATIVE STATISTICS
• What is comparative statistics
HYPOTHESIS TESTING
• Null and Alternate Hypothesis
• P value
2
DECIDING WHICH STATISTICAL TOOL TO USE
• Dependent and Independent variable
• Identifying nature of variables
• Identify normality
PRACTICAL SESSIONS
• Chisquare test
• T test
• ANOVA
• Pearson Correlation

3. “
Science and statistics are
companions. You need the statistics to
back up the science, and you need
science to back up the statistics.
FORTUNE EFFIONG
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4. What is comparative statistics?
◉ Comparative statistics allows the comparison of groups of
samples to identify differences or similarities.
◉ It looks at association between two variables
◉ Hence, comparative statistics is concerned with (tests) two
things:
◉ (1) IF THERE IS AN ASSOCIATION BETWEEN TWO VARIABLES
◉ (2) IF THIS ASSOCIATION IS SIGNIFICANT
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5. Comparative Statistics
◉ Comparative statistics makes use of statistical tools to
answer its questions
◉ BUT how do we know which tool to use in answering a
particular question?
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6. DECIDING WHAT
STATISTICAL TOOL TO
USE
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7. T test, Chisquare,
ANOVA, Correlation?
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8. DECIDING THE STATISTICAL TOOL TO USE: THE PROCESS
IDENTIFY THE TYPE
OF VARIABLE
IDENTIFY THE
NATURE OF
VARIABLE
IDENTIFY THE
NORMALITY OF
THE DATA
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9. IDENTIFYING THE TYPE OF
VARIABLE
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Dependent and Independent variable

10. INDEPENDENT VARIABLE
◉ It is the one the experimenter controls.
◉ The independent variable is the
cause. Its value is independent of
other variables in your study.
◉ Independent variable is the variable
that is changed (by the researcher).
DEPENDENT AND INDEPENDENT VARIABLE
DEPENDENT VARIABLE
◉ It is the variable that changes in
response to the independent
variable.
◉ The dependent variable is the
effect.
◉ Dependent variable is the variable
affected by this change.
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11. 11
• The dependent variable depends on the independent variable.
• Because it depends on the independent variable, it changes
across test subjects or study participants.
• It is the variable that is measured, hence, it is also
called measurable variable.
• Sometimes, the Independent variable is considered
as the GROUPING/MANIPULATED variable.
DEPENDENT AND INDEPENDENT VARIABLE

12. ◉ “To determine if syphilis in pregnant women is associated with age
and occupation”
◉ “In a study of how different doses of a drug affect the severity of
symptoms, a researcher could compare the frequency and intensity
of symptoms when different doses are administered.”
◉ “To determine the influence of sociodemographic characteristics on
knowledge of hypertension of Nigerian youths”
◉ “To determine association between field of study and willingness to
take the malaria vaccine”
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DEPENDENT AND INDEPENDENT VARIABLE
PRACTICE EXAMPLES

13. ◉ “To determine the effects of high cost of menstrual pad on women’s menstrual
hygiene”
◉ “Association between intestinal nematodes prevalence with gender and age”
◉ “To ascertain the difference in haematological parameters among those that smoke
marijuana and non user’s”
◉ “To evaluate Haemoglobin, Platelet count, and fibrinogen in malaria infected
pregnant women and compare with controls
◉ “To investigate the effect of gestation age(1st, 2nd and 3rd trimester) on
Haemoglobin, platelet count and fibrinogen”
◉ “Does the type of ART of HIV patients affect haematological parameters (like PT,
APTT and PLT”
13
DEPENDENT AND INDEPENDENT VARIABLE
PRACTICE EXAMPLES

14. IDENTIFYING THE NATURE
OF VARIABLE
Continuous, Discrete and Categorical 214

15. CONTINUOUS, DISCRETE, CATAGORICAL VARIABLES
Continuous variables
can take any numerical
value and are measured.
Eg Haemoglobin values
Discrete variables can
only take certain
numerical values and
are counted. Eg
age(21,23,24), number
of spouse
Categorical variables involve
non-numeric groups or
categories. Eg age (21-25,26-
29), sex, awareness of
covid19 vaccine (either yes or
no), perception of monkeypox
virus (SA, A, N, D, SD)
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16. IDENTIFYING THE NORMALITY OF
THE CONTINUOUS VARIABLE
Parametric and Non-Parametric tests 316

17. Parametric tests are used for data that are assumed to be normally distributed.
Parametric tests assume that the sample distribution is about the same shape and has the same
parameters(mean, SD) as the population.
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4000
3000
2000
1000
0

18. Non parametric test are used for data that are not normally distributed.
18
4000
3000
2000
1000
0

19. The main tests for the assessment of normality are:
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Shapiro-
Wilk test
Kolmogorov
-Smirnov
(K-S) test
Lilliefors
corrected K-
S test
Cramer-
von Mises
test,
D'Agostino
Anderson-
Darling
testskewness
test
D'Agostino
-Pearson
omnibus
test
Anscombe
-Glynn
kurtosis
test
Jarque-
Bera test

20. 20
PARAMETRIC TEST NON-PARAMETRIC EQUIVALENT
Paired t-test Wilcoxon Rank sum Test
Unpaired t-test Mann-Whitney U test
Pearson correlation Spearman correlation
One way Analysis of variance(ANOVA) Kruskal Wallis Test
PARAMETRIC AND NON-PARAMETRIC TESTS

21. THE PARAMETRIC TESTS CHART
INDEPENDENT
VARIABLE
DEPENDENT VARIABLE
CATEGORICAL CONTINUOUS
CATEGORICAL Chisquare test ANOVA/t-test
CONTINUOUS Logistic
Regression
Pearson
Correlation
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22. ◉ “To determine whether syphilis in pregnant women is associated
with age and occupation”
◉ “In a study of how different doses of a drug affect the severity of
symptoms, a researcher could compare the frequency and intensity
of symptoms when different doses are administered.”
◉ “To determine the influence of sociodemographics characteristics
on knowledge of hypertension on of Nigerian youths”
◉ “To determine association between field of study and willingness to
take the malaria vaccine”
◉ “To determine the association between PT and APTT levels in
smokers.”
22
DECIDING STATISTICAL TOOL TO USE
PRACTICE EXAMPLES

23. ◉ “To determine the effects of high cost of menstrual pad on women’s menstrual
hygiene”
◉ “Association between intestinal nematodes prevalence with gender and age”
◉ “To ascertain the difference in haematological parameters among those that smoke
marijuana and non user’s”
◉ “To evaluate Haemoglobin, Platelet count, and fibrinogen in malaria infected
pregnant women and compare with controls
◉ “To investigate the effect of gestation age(1st, 2nd and 3rd trimester) on
Haemoglobin, platelet count and fibrinogen”
◉ “Does the type of ART of HIV patients affect haematological parameters (like PT,
APTT and PLT”
23
DECIDING STATISTICAL TOOL TO USE
PRACTICE EXAMPLES

24. HYPOTHESIS TESTING
In comparative statistics
◉ Null Hypothesis (H0) states that there is no association
between the variables in question.
◉ Null hypothesis argues that if there is any association, it is by
chance and not due to the experimental conditions.
◉ Alternate Hypothesis argues that the association is not by
chance
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25. HYPOTHESIS TESTING IN COMPARATIVE STATISTICS: P value
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P value calculates the probability that the event
(association) occurred by chance.
P value of 1 means certainty – that the event definitely happened due to
chance. P value of 0 means that the event can never happen by chance
Null Hypothesis is true if P value is above the
alpha/reference point (0.05 or 0.01 in most research)

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If P value is less than
0.05
Result is significant.
Reject Ho
The P value chart
If P value is greater
than 0.05
Result is not significant.
Accept Ho

27. ROADMAP FOR PRACTICAL VIDEOS
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1 3 5
6
4
2
Chisquare ANOVA
Logistics
regression
T test Pearson
Correlation
Summary
Video

28. THANK YOU FOR YOUR TIME
+2349097015368 Fortune Effiong
on all SM handles (FB,
LinkedIn, Twitter)
effiongfortuneb@gmail.com
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