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Transcript of Non – Parametric Test Dr.L.Jeyaseelan Dept. of Biostatistics Christian Medical College Vellore,...
![Page 1: Non – Parametric Test Dr.L.Jeyaseelan Dept. of Biostatistics Christian Medical College Vellore, India.](https://reader030.fdocuments.in/reader030/viewer/2022032723/56649f535503460f94c77703/html5/thumbnails/1.jpg)
Non – Parametric Test
Dr.L.JeyaseelanDept. of Biostatistics
Christian Medical CollegeVellore, India
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IntroductionIntroduction
No rigid assumptions about the distribution of the populations - “Distribution-free tests”
Answers the same sort of questions as the parametric test – for each Parametric tests (PT) there is an alternative Non-Parametric Test (NP) Test
Applied to a wide variety of situations continuous ordinal scores
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Assumptions of parametric test are violated
When are non-parametric tests used?When are non-parametric tests used?
Non-normal or skewed
Variance very high in relative to mean
Data is on an ordinal scale
Very few observations
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Mann-Whitney U Test
Most powerful of the NP test – Wilcoxon Rank Sum test
Alternative to the parametric independent t-test
To test whether two independent groups have been drawn from the same population
Assumptions:
Two sample are selected independently and at random from their respective population
Variable of interest is continuous
Measurement scale is at least ordinal.
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Mann-Whitney U Test
HHoo:: There is no significant difference between the medians There is no significant difference between the medians of the two samplesof the two samples
HHaa:: There is a significant difference between the medians There is a significant difference between the medians of the two samplesof the two samples
Compare the distribution of scores on a quantitative variable obtained from two independent groups.
Group A : 2 4 2 6 4 8
Group B : 8 8 4 10 12 11
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Man Whitney U test output
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Mann-Whitney U Test (contd.)
A researcher designed an experiment to assess the effects of prolonged inhalation of cadmium oxide. 15 lab animals served as experimental subjects while 10 similar animals served as controls. Variable of interest was Hb level following the experiment. Conclude that there is no difference between exposed and unexposed animals in their Hb level
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sno
Exposed Unexposed
1 13.1 17.4
2 15.6 16.2
3 17.3 17.1
4 16.4 17.5
5 14.3 15
6 15.5 16
7 14.9 16.9
8 15.6 15.1
9 14.1 16.1
10 15.3 17.2
11 15.7
12 16.7
13 13.7
14 15.6
15 14
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Deciding Normality
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Conclusion???
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Large Sample: When n1,n2 > 10 (normal approximation)
The test statistic is given as
12)1(
2
2121
21
nnnn
nnU
Z
)var(
)(
U
UEUZ
where ‘U’ is the smallest sum of ranks between U1 and U2
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Wilcoxon Signed-Rank Test
An alternative to the parametric paired t-test Used to compare 2 samples from populations are not
independent eg., measure a variable in each subject before and after an intervention
Assumptions Samples must be paired Pairs are randomly selected from the larger population Probability distribution from which the sample of paired
differences drawn is continuous
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Below is the measurement of anxiety before and after two weeks of treatment.
SNO
BEFORE Rx
AFTER Rx
1 130 120
2 170 163
3 125 120
4 170 135
5 130 143
6 130 136
7 145 144
8 160 120
Does the treatment have any beneficial effects?
Wilcoxon Signed-Rank Test
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Result???
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Exercise: Wilcoxon signed rank Test
Examine whether there is any significant
difference in the systolic blood pressure of 16
subjects before and after receiving a standard
treatment
Sno Before
After
1 142 143
2 148 146
3 144 147
4 142 138
5 140 136
6 144 139
7 146 141
8 150 145
9 149 143
10 142 136
11 149 145
12 143 140
13 145 143
14 146 142
15 143 140
16 146 141
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Result???
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Nonnumeric data such as Taste of food: bad, good, great and excellent, Smoking habit: light, moderate and heavy etc.
Involves simpler computations than the corresponding parametric methods and are therefore easier to understand.
Since the inference is based on ranks, Nonparametric methods are quick for small samples and less subject to measurement error than parametric methods.
Advantages of Nonparametric Methods
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Disadvantages of NP Methods
No parameters to describe and it becomes more difficult to make quantitative statements about the actual difference between populations
Tend to waste information because it deals with ranks and discard the actual values
Less powerful where parametric test is applicable.
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Selecting a Statistical Test
Type of Data
Measurement from Normal Population
Rank, Score or Measurement from
Non-normal
Describe one group Mean, SD Median, Interquartile Range
Compare two independent groups
Independent sample t-test (unpaired t test)
Mann-Whitney test
Compare two paired groups
Paired t test Wilcoxon Signed rank test
Quantify relation between two variables
Pearson Correlation Spearman Rank Correlation