2. Data entry 3. Data cleaning
4. Data transformation
SCENARIO LEARNING TASKS
Case. A population study was done in two sub villages in Desa Merdeka. This study’s purpose
was to determine several factors that associated with anaemia and chronic malnutrition among children in the area. The area has two different characteristics which are easy to
reach area easy and hard to reach area hard. The condition of both areas was suggested to be considered since there might be different characteristics of the family;
hence, the samples were randomly selected from both areas.
First Phase
Data collection was performed by interview using structured questionnaire with the mothers and measurement of the children see questionnaire in the skill lab guide. The
characteristics that were explored and measured include: mothers’ and children’s demographic characteristic, haemoglobin level and body weight. More specifically, the
variables in the study were ID, name, area, mothers’ age, education, occupation; parity; and children’s age, haemoglobin level, body weight and height. The haemoglobin level
measured with HemoCue, and body weight measured with digital scale. Anaemia status was determined when Hb level less than 11 mgdl and undernourished determined when
BMI less than 11kgm
2
Second Phase
After the above data collection was completed, the second phase of the study was started. This phase aims to evaluate the impact of food supplementation program to
improve nutritional status among undernourished children. All undernourished children were involved in the study, expect those with severe illness. The children were allocated
into two groups; first group received food supplementation and second groups continue with the prior daily consumption. The supplementation was provided up to 2 months and
at the end of two month the nutritional status the body weightwere measured again.
Learning Tasks:
See the sheet of data collection and raw data. The data were analysed by computer with software of SPSS. Discuss and analyse the tasks bellow:
1. Explain the types of variables in relation to construction of data entry: variable name name, type, width, decimal, labels, value labels, missing values
2. Number No consists of 3 numbers hundreds, name of its field is: number 5
characters, not more than 8 characters for SPSS V.12 or bellow. Fill in the following field structure: type of field: . . . . . . . . . . . . ; Width: . . . . . ; Decimal: . . . . . . . . ,
Labels: . . . . . . . . . . . . . . . . . . . . . . . . . . , Value labels: . . . . . . . . . . . . . . . . . . . . . ; Missing values: . . .
3. Generally, how can you determine errors in data entry? 4. Explain how you can search and fix the errors
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5. Explain the methods of classifying interval and categorical data 6. Explain how to calculate composite index of Mass Body Index based on body height
and body weight.
Self Evaluation
1. A haemoglobin value consists of 2 numbers and 1 decimal example: 13.6 gr.
What is its field width? 2.
Explain the limits of values that can be used as indicators of error in data entry. 3.
Explain the types of variables based on their functions. Give an example of each variable.
4. Explain the types of variables based on measurements scale. Give an example of
each. 5.
Explain with an example, what is the meaning of ratio variable? 6.
Explain some methods to control a variable 7.
Explain the differences between formal education and IQ variables
M O D U L E ~ 6
Reference Greenberg, p. 29-43
Analysis and Interpretation of Descriptive Data
dr. Ida Bagus Wirakusuma, MOH dr. Putu Ariastuti, MPH
AIMS:
To demonstrate ability to search, collect, organize and interpret informationdata from different sources in order to assist in diagnostic, therapeutic and health.
LEARNING OUTCOMES:
1. To analyse, present, and interpret descriptive data. 2. To interpret the measurements of morbidity and mortality on samples
descriptively
CURRICULUM CONTENTS:
1. Variable of person, place, and time
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2. Rate comparison 3. Data interpretation
ABSTRACT
Descriptive in epidemiology begins with the assumption that disease do not occur in random. Typically three standard questions are posed to characterize the non random
distribution of disease: Who get the disease? Where does the disease occur? and When does the disease occur? These questions concern the element of person, place
and time, respectively.
At the minimum, the personal attributes examined in relation to disease occurrence are the distribution by age, race and sex. The place of occurrence of the
disease may be studied at international, regional and local level. Temporal pattern can be examined across year, month, or days, depending on the time course of the disease
in question.
SELF DIRECTING LEARNING:
Basic knowledge and its application that students must know include: 1. Variables of person, place and time
2. Rate comparison and interpretation
SCENARIO LEARNING TASKS
Case 1. Look at the following figure carefully:
Fig 1 Total deaths by broad cause group, by WHO Region, World Bank income group and by sex, 2008
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Source: Global status report on non communicable diseases 2010
Learning Tasks 1: Carefully look at the figure above, and discuss the following questions:
1.
What are the interpretations of the figure? How many conclusions could you drawn from the figure?
2.
When you are living at Indonesia on 2008, what is your risk of death by injuries?
Case 2. Carefully look at the figure below, and discuss the following questions:
Fig. 2 Most frequently diagnosed cancers world wide
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Source: Global status report on non communicable diseases 2010
Learning Tasks 2:
1. The figures are data of cancer worldwide based on 1 ………; 2 ……….; 3 ………… 2. Could we conclude that risk of lung cancer among male is higher than liver cancer
among female? 3. Could we conclude that risk of breast ca among female is higher than cervix ca?
4. Could we conclude that risk of lung cancer in Indonesia is higher than in India?
Case 3:
Figure 3. Age-standardized incidence of all cancers excluding non-melanoma skin cancer, by type, per 100 000 population for both sexes, by WHO Region, 2008
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Learning Tasks 3: Based on the above figure, please answer the following questions:
1. The figures are data of cancer worldwide based on 1 …………….; 2 …………..
2. Could we conclude that highest risk of lung cancer was in AMR and EUR?
3. Could we conclude that risk of breast ca among female is higher than cervix ca?
4. Could we conclude that risk of cervix uteri cancer in SEAR is higher than in
AFRICA? 5.
What are the difference between data provided at figure 2 and 3?
Self Assessments:
1.
What is the definition of specific rate?
2.
What are the differences between specific and crude rate?
3.
Which variables are usually used as a base for specific rate calculation?
4.
What is the usebenefit of calculating specific rate?
5.
Describe the method to diagnose an undernourish problem among under-five- year old children in one area?
6.
A clinician needs to understand the variation pattern of diseases based on Who, Where, and When. Why?
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M O D U L E ~ 7
Reference Kirkwood Sterne, Chap 3 4
Data Presentation and Data Description
dr. Putu Ayu Swandewi, MPH dr. Gede Artawan Eka Putra, M.Epid
AIM:
Demonstrate ability to search, collect, organize and interpret informationdata from different sources in order to assist in diagnostic, therapeutic and health.
LEARNING OUTCOME:
Be able to perform data presentation and data description.
CURRICULUM CONTENTS:
Data presentation and data description
ABSTRACT
Presenting and describing data are closely related with data classification based on their function, which are: interval numeric or quantitative, discrete, continue, categorical
qualitative, and ordinal data.
Qualitative data is divided into two categories dichotomies and more than two categories multi-chotomies. Important aspect of qualitative data is the number for each
category. The analysis can be made is, either frequency distribution or cross-tab frequency distribution. In the table of frequency distribution, we can calculate incidence,
prevalence, and ratio, both for crude and specific measurements based on place, time and person. To summarize the data we can use highest and lowest frequencies and or
mode. While for cross-tab frequency distribution, we can make percentage based on column, row, dan total percentages. For specific cross-tab 2x2 four-fold table, we can
calculate some important indicators such as Odds Ratio OR, Risk Ratio RR, Specificity Sp, and Sensitivity Se. Besides table, we can present this data by graphic,
which is most appropriate, is bar chart
Presenting numericquantitative data looks more simple than presenting categoricalnominal data. The important aspect to be understood is how to determine
appropriate data presentation, either as a single variable or in relation with other variable. Measurements which are used is central tendency Average and dispersion.
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Including in average are mean, mode, median, strength and weakness of average. While including in dispersion are range, variance, SD; strength and weakness of dispersion.
This data can be displayed in graphic such as line chart, hystogram, and box plot.
SCENARIO:
Case 1. Data Presentation of Categorical Data
Look at the skill lab Data appendix Data which have been collected, include several variables: area, age, education level, occupation, exclusive breastfeeding, parity,
children age, Hb level , body weight and height. In the previous session, we’ve discuss variables based on their scale of measurement. Understanding the measurement scale
of data is important for selecting the way to present the data. .
For categorical data, the presentation mainly using three different mode which are table, graphchart and statistics. Table for categorical data are single frequency table, and
cross table. Presentation of categorical data in graph can used either bar or pie chart; and statistics that is used are percentage or ratio.
Learning Task 1
Discuss the following:
1. Discuss data presentation in a table andor chart; and explain the components of
