M O D U L E ~ 10
Reference Kirkwood Sterne, Chap. 7, 9, 11, 16, 18, 19
Significance Test for Categorical and Interval Data
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:
Understand the significance test for categorical and interval data
CURRICULUM CONTENTS:
Significance Test for Categorical and Interval Data
ABSTRACT
1. CATEGORICAL DATA
For analytical test, we must remind classification of variables based on their function to determine which variable act as dependent or independent variable.
In a sample taken from certain population, we can calculate proportion, rate, or ratio. Those numbers are used to estimate the parameters in a population. To know
whether those numbers are accurate to estimate population parameters, we need to conduct hypothesis test. When conducting the hypothesis test, we need to state
statistic hypothesis. There are two types of statistic hypothesis, are null hypothesis H
which shows no difference similar in a population, and alternative hypothesis H
a
which shows there isare differences not similar in a population. The way to write those hypothesis are depending on the study direction and indicator to be
measured.
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Statistical tests for categorical data include test for 1 proportion binomial test, two proportions Chi-square, Mc Nemar, Fisher exact, and three proportions or more
Chi-square. Each of those has requirements to be fulfilled before the test being conducted. In some tests, if the requirement is failed to be fulfilled, there are available
the alternative test.
2. INTERVAL DATA
For interval data, the indicators to be calculated in statistical test are mean or median. Statistical hypothesis also stated in H
andH
a
in a ways depend study direction and the indicator measured. Requirements for statistical test on interval
data are data must be normally distributed and the variance between the groups tested are similar.
Statistical tests for interval data include test for mean of 1 sample One-sample T- test, Independent-Sample T Test for unmatched 2 samples and Paired-Sample T
Test for matched 2 samples if the analysis is conducted for one dependent interval variable with one dichotomous categorical variable. If the data is not normally
distributed, we may choose parametric test such as Mann Whitney U Test, Wilcoxon Wilcoxon Sign Rank
While for analysis of one dependent interval variable with one multicotomous more than 2 categories variable, the choice are One-Way ANOVA if normally distributed,
comparative group test Bonferroni, LSD, Scheffe etc if variance is similar, Tamhane’s T2T3 etc if variance is not similar, and non parametric test Kruskal-
Wallis if the data is not normally distributed.
SCENARIO:
Case 1.
Significancy Test for Categorical Data
Re-open skill lab data annex. Data available in the data set include: area, age, education level, occupation, exclusive
breastfeeding, parity, children age, Hb level, and body weight. Let’s recall that understanding the measurement scale of data is important for selecting the way to
present the data. Beside for purpose of data presentation, measurement scale of data is important on determining the appropriate type of statistical testing hypothesis testing.
Moreover, the classification of data based on the function in the relationship is also important issue to be considered.
We have discussed that there are mainly two type of hypothesis testing which are testing the association and testing the difference comparison. In the previous section, we
learned about correlation test which is one type of test for testing association between variables. In this section, we will discuss hypothesis test for the difference comparison.
The testing will be differentiating based on the type of data categorical or continuous data.
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From a sample taken from a population, we can calculate proportion, rate, and ratio. These numbers are parameter estimations of a population. Whether a number gained
from sample may or may not represent its population, it needs to be verified by statistical methods towards the hypothetical test. There are two kinds ofhypothetical statistic
statements: Null Hypothesis H
and Alternative Hypothesis H
a
. The Null Hypothesis H
assumes that there is no difference similarity in a population, while
the Alternative Hypothesis H
a
assumes the opposite.
Learning Task 1
1. Discuss about null hypothesis and alternate hypothesis, and provide example of hypothetical testing based on the skill lab data
2. Discuss two type of error in making decision on statistical analysis 3. Discuss about the p value and its use in statistical testing?
4. Discuss
a. If the p value of a test is 0.01, what does it means? b. if the p value of a test is 0.1, what does it means?
5. If from the study we found that the prevalence of malnutrition in Desa Merdeka is 12. Can we conclude that the proportion is different from national data which is
at 10. ? α=0.05 Discuss:
a. The statistical hypothesis of case 1 b. The statistical test should we apply for the analysis of case 1
c. How we determine the statistical decision d. If the p value for the study is 0.1, what is your decision and interpretation
6. We want to compare the proportion of undernourished children from hard area 1 and easy area 2. α=0.05. The proportion of undernourished children in
hard area and easy area is 18 and 15, respectively. Discuss:
a. The statistical hypothesis for testing there is a different between both area b. The statistical hypothesis for testing that the proportion of undernourished
children is higher in the hard area compare to the easy area c. The test should we apply for the analysis
d. Create the 2x2 table for this case e. If p value from the study is 0.005, what is the statistical decision and
conclusion of the analysis 7. We want to determine wether obesitas is a predictor of diabetes millitus DM
among men age above 40 years olds. A cross-sectional study was conducted;
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among 100 men above 40 years old; 40 of them are obese. Among those 40 with obese 20 of them are diagnosed with DM; meanwhile among the remaining 60
men, 15 of them are diagnosed with DM. Discuss:
a. The statistical hypothesis for testing for determining that obesitas is predictor of DM
b. The test should we apply for the analysis c. Create the 2x2 table for this case
d. Calculate the ratio of riskodd that appropriate based on the study design e. If the 95 CI of the above ratio is between 0.8- 3.5, what is the statistical
decision and conclusion of the analysis
Case 2 Significancy Test for Interval Data
Open again “skill lab data” file annex. Classification of variables has been discussed in previous lesson. Remember about interval variables For statistical analysis, we also
need to remember variable classification based on its function. Variables may act as dependent or independent variables.
The statistical analysis is classify into two group which a parametric test and non parametric test. Parametric test based on the assumption of the distribution of the data.
For continuous data that are normally distributed, the statistical analysis includes t test and ANOVA. The tests principally based on comparison of mean between groups.
Learning task 2
Discuss the following: 1. Discuss the statistical method to be applied for testing of a sample mean.
We want to compare the mean Hb level of pregnant women in the study, with the normal Hb level for pregnant women which is 11mgdl. Can we conclude that the
mean of Hb level of samples is higher than 11 mgdl?
a. Write down the statistical hypothesis b. Discuss, the test that should be applied for the analysis
c. How we determine the statistical decision
2. Discuss about when two groups of samples data considered as two independent or two dependent samples?
3. Discuss about homogeneity of variance and when we should determine it? 4. What type of test is used for testing homogeneity of variance, provide an
illustration 5. We want to compare the mean body mass index BMI among children from hard
area and children from easy area. We wish to conclude that the mean BMI of children in hard are is higher than the children in easy area. Let α=0.05
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a. Write down the statistical hypothesis for case 2 b. Explain what test should be applied for the analysis of case 2
c. If the p value from the study is 0.09, what is the statistical decision and
conclusion of the analysis? 6. We want to evaluate the impact of nutrition program on the body weight among
the children in the study. Can we conclude that the intervention is effective to increase the children’s body weight? Let α=0.05
a. Write down the statistical hypothesis for case 3 b. Discuss the test should be applied for the analysis for case 3
d. If the 95 confidence interval of body weight mean difference is 1.2 to 2.8 kg,
what is the statistical decision and conclusion of the analysis?
7. We want to compare the mean Hb level pre intervention Hbpre of children based on the nutritional status pre intervention stgizi_pre. Can we conclude
that the mean body weight differ based on nutritional status? Discuss:
a. What test should we apply for the analysis? b. Is the analysis one tail or two tails?
c. Write down the statistical hypothesis d. If the p value from the test is 0.2, discuss about the statistical decision and
the conclusion. 8. Explain the conditions for applying those statistical tests above
If the conditions cannot be met, what statistical method should be applied for testing the hypothesis?
Self Assessments:
Significance Test for Categorical Data
1. Explain the statistical method for 2x2 tables and its requirements. 2. Explain the statistical methods if those requirements are not fulfilled
3. Explain the statistical method for pair 2x2 tables. 4. Describe the statistics that can be calculated in 2x2 tables for cross-sectional, case-
control, and cohort study. 5. Write down the statistical hypothesis statement
6. Explain the statistics for correlation of two variables: interval-interval, ordinal-ordinal, nominal-interval, nominal-nominal, and similar number of categories.
7. Explain the condition for
2
test of the 2x3 tables or more. Explain how to deal with that if those conditions are not provided.
8. Write down the statistical hypothesis statement for proportion, prevalence, RR, PR, and OR for one-way and two-way tests.
9. What is the meaning of type 1 and type 2 sampling error?
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Significance Test for Interval Data
1. Explain the application and requirements for one sample T-test 2. Which T-test should be applied for independent and pair samples?
3. Write down the statistical hypothesis statement used above 4. Regarding the tests above, which tests should be used if the condition required for T-
test is not met? 5. Explain the non-parametric test to be applied if the condition required for the
independent One-Way ANOVA is not met. 6. Write down the statistical hypothesis statement for the above question
M O D U L E ~ 11 SKILL LAB III
Skill Lab Manual, Kirkwood Sterne
Correlation-Regressi, Significance Test for Categorical and Interval Data
dr. Putu Ayu Swandewi, MPH dr. Gede Artawan Eka Putra, M.Epid
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 conduct data analysis correctly for categorical and interval data 2. To interpret data accurately
CURRICULUM CONTENTS:
1.
Data analysis for categorical and interval data
2.
Data interpretation for categorical and interval data
SCENARIO LEARNING TASKS
Refer to Cases of Data analysis and data interpretation for categorical continues data DAY 12.
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M O D U L E ~ 12
Reference Greenberg, p. 45 – 73
Definition, Requirements, Types, and Applications of Surveillance and Outbreaks
dr. Ayu Kartika Sari, MPH dr. Putu Ariastuti, MPH
AIM:
Demonstrate ability to search, collect, organize and interpret informationdata from different sources in order to assist in diagnostic, therapeutic and health.
LEARNING OUTCOMES:
At the end of the module, students should be able to: a Manage, analyze and interpret data inferentially.
b Describe the definition, requirements, types, and applications of surveillance. c Describe how to conduct an epidemiologic investigation of an outbreak.
CURRICULUM CONTENTS:
Surveillance and Disease Outbreak
ABSTRACT
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SURVEILLANCE
Surveillance was defined as the detection of the occurrence of health-related events or exposures in a target population. Successful surveillance activities require continuity
over time; standardize methodology, and timelines of data collection and dissemination.
Surveillance data can be used in different ways, depending on the type of information collected. Persons newly diagnosed with a disease can yield information on
incidence rate, death from a disease can be used to describe mortality rate, indices of premature death can be used to assess the impact of a disease of longevity, and
prevalence of risk factors can be used to predict future disease occurrence or to assess the status of prevention initiatives.
OUTBREAKS The investigation of disease outbreaks sudden and geographically limited epidemics is
an essential role epidemiology. The primary goals of an outbreak investigation are the identification of the causal agent the pathogen and prevention for further cases. The
propagation of a disease outbreak requires a pathogen, a viable mode of transmission, and an adequate poll of susceptible persons. Elimination of one or more of these three
components will terminate the outbreak. Two basic modes of transmission are person-to- person spread and common-source exposure. Infection illnesses can be transmitted by
either mode, whereas non-infectious environmental pathogens usually produce disease outbreaks through a common-source transmission.
Not all disease outbreaks warrant investigation. The decision to investigate an outbreak typically is based on the severity of illness, the number of affected persons,
uncertainty about the pathogen, and the perceived need to control further spread of the disease. Investigations usually are conducted by local, state or federal public health
officials.
A measure of the risk of developing an illness over specified period of time is the attack rate AR. The traditional epidemiology of food-borne outbreaks-high attack rates,
short incubation periods, and clustering of affected individuals in time and place-is changing for a number of reasons. The composition of the topical diet has shifted, with
decreased consumption of red meat and increased consumption of poultry, fresh fruits, and vegetables.
Emerging infections can be defined as infections that are appearing in a population for the first time or that have existed in a population but rapidly increasing in
incidence or geographic range. A number of factors contribute to the emergence of certain infections:
1 Man-made or natural changes in the environment 2 Demographic shift in population
3 Increased international travel and commerce 4 Technologic and industrial changes.
5 Adaptation of microbes 6 Lapses of the public health system.
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Self Directing Learning
1. Read previous lectures 2. Read Greenberg pp. 45-73and power point slides
3. Watch the “Contagion” movie
SCENARIO LEARNING TASKS
Case 1 Learning Task 1
Interpretation of Surveillance Results
The following chart contains results of surveillance of dengue hemorrhagic fever in Bali Province, provided by the Bali Provincial Health Department.
Discuss the following questions: 1. The surveillance is conducted to assess morbidity, mortality, or risk factor of dengue?
Explain your answer. 2. What is the interpretation of the figure?
3. What is the benefit of conducting surveillance of dengue cases? 4. Think of the natural history and the determinant of DHF and also consider the types
of surveillance. What other surveillance might needed for the success of the dengue prevention program?
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Case 2. Watch the movie “Contagion” and read the synopsis below Synopsis of the movie: “Contagion”
1. This movie is a fiction which inspired by the incidence of SARS in several countries around the world.
2. The story is about an outbreak of an unknown disease occurred initially in China and spread to other places including the USA, Japan and England.
3. The movie shows how a disease can be transmitted very fast to cause an outbreak all over the world, how the mode of transmission and the causing agent can be
identified, and how the transmission can be finally prevented. 4. The story is started with a woman named Beth Emhoff Gwyneth Paltrow departing
to Minnesota from her Chicago layover. She had a short term visit to Macao near Hong Kong beforehand. She seemed to cough several times at the airport when
she talked to her old boyfriend on the phone.
5. The story was continued with the occurrence of a severe flu-like disease in a young man in Hong Kong who then died because of a traffic accident, in a young model in
London who then found dead in her bathroom and in a man in Tokyo who had a seizure and died on a bus.
6. The same symptoms that happened to Beth got worsened once she arrived in Minnesota and met her husband and son. She died in a hospital 2 dayslater with
severe seizures and the doctor decided to make an autopsy to her body. Soon after her death, her son died after having the same symptoms.
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7. Beth’s husband, Mitch Matt Damon, was then put in isolation but turned out to be immune to the disease.
8. In Switzerland, a briefing led by Dr. Leonora Orantes Marion Cotillard was conducted at the WHO office. She emphasized the need to investigate the cases of
infection thoroughly and thought that Beth is the potential start of the infection. She then went to Hong Kong to investigate the movements Beth made while there.
9. Dr. Ellis Cheever Laurence Fishburne, who works at the Atlanta-based Centers for Disease Control and Prevention CDC, asked Dr. Erin Mears Kate Winslet to do
an investigation in Minnesota. She gave a briefing at the nearby CDC office about the potential mode of transmission of the disease. She said that the virus is a
contagion of touch and the problem is the number of people will be potentially infected R-naught number, which is very high for this novel disease. She was then
unfortunately infected and died during the investigation.
10. There was an issue released by a blogger journalist, Allen Jude Law, that the virus is being manufactured by drug companies to get profit. Another issue said by
Homeland Security agents was that the virus might be a terrorist action to kill people.
11. Two doctors, Ally Hextal Jennifer Ehle and David Eisenberg Demetri Martin looked at the samples taken from Beth’s body in a secure CDC bio laboratory. They
found a virus that taking over the host cell completely, and noticed there were traces of bat and pig in the virus DNA code.
12. Dr. Sussman Eliott Gould ran some further tests on the virus samples and he was able to make a stable cultured version of the virus using a particular bat cell line.
This finding made them able to develop and test vaccines. The news reported on the virus, now called MEV-1 Meningoencephalitis virus type 1, and credited
Sussman for the discovery.
13. The story continues with the situation of the quarantine and vaccines delivery process to prevent the transmission of the disease. Finally the movie shows the
process of how Beth was initially infected by the virus.
Learning Task 2
Based on the story of the movie, please answer the following questions: 1. What is the type of the disease outbreak in the movie? Is it a “person to person
outbreak” or a “common source outbreak”? Please explain your answer. 2. Why is it important to find the first person being infected? Describe how the
process of identifying the mode of transmission was conducted in the movie. 3. What efforts need to be taken to prevent the disease transmission before the
vaccines are available? 4. Describe how the process of finding the virus was conducted in the movie.
5. What is the importance of many stakeholders involvement WHO, CDC, government, military staff and journalists in the outbreak investigation and
transmission prevention process?
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Self Assessment
Interpretation of Surveillance Results
1. The government continuously collects data for smoking behavior among men
and patterns of meat consumption among both men and women. In this case, what the government does is:
A. New infections surveillance B. Outbreaks surveillance
C. Death surveillance D. Risk factors surveillance
E. Epidemiologic surveillance
2. A group of Lung Cancer patients who died were identified for their age of
death. The difference between the age of death and their average life expectancy was then accumulated. That will produce:
A. PYL Person-years of Life lost.
B. MR Mortality rate.
C. YPLL years of potential life lost.
D. YPM Years of mortality
3. 60 of lung Cancer patients in stage 2 have the possibility of survival for five
years following diagnosis of the cancer. The measurement of 60 follows the criteria as below:
A. It is a case fatality rate of Lung Cancer patients B. Can be used to predict the prognosis of Lung cancer patients in a similar stage.
C. It was measured from the lung cancer patients in one periode of time into Lung
cancer patients’ stage 1 – 3. D. One person with Lung cancer stage 2 having possibility to live in the first five
years as of 0.06. E. All Lung cancer patients’ stage 2 may live five years after diagnosed.
4. When compared to the corresponding rate for non-migrants in a low risk country, the incidence rate for a genetically determined disease among offspring in a high-risk
country is: A. Greater
B. Smaller C. About the same
D. Cannot be determined from the information provided E. All possible
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Outbreak Investigation
1.
Which steps of those above are parts of descriptive methods? Which are parts of analytic methods?
2. Not all outbreaks need epidemiologic investigation. Several factors to be considered for an investigation are:
1. Number of apparent cases prevalent 2. Public concern
3. Aetiology of the outbreak is obviously unclear 4. Need for intervention to be stopped
3. The following are parts of the outbreak investigation steps: 1. Distribute cases based on person, place and time
2. Calculate prevalence rate based on person, place and time 3. Assume temporary hypothesis on transmission’s source
4. Analyse aetiology by cross sectional study
4. Due to the outbreak investigation, the analysis of cases based on person, place, and time is done. Its main purpose is:
1. Find out the most common group affected by the disease 2. Find out the area which was mostly affected by the disease
3. Determine the time of outbreak 4. Predict the possibility of exposure
5. A result of outbreak investigation is as follows: Risk Estimate
Value 95 Confidence Interval
Lower Upper
Odds Ratio for Stall B Yes No 0.048
0.016 0.145
For cohort Sickhealthy = Yes 0.231
0.130 0.410
For cohort Sickhealthy = No 4.846
2.307 10.181
Its interpretation is: a.
Risk of diarrhea if having meals at B stall is a half lower than not having meals at the other stall.
b. Risk of diarrhea if having meals at B stall is higher than not having
meals at B stall. c.
The OR only affects sample, but not a population. d.
The B stall is proven not to be source of transmission. 6. If an OR of eating “es campur” at the B stall is 1.3 with the CI from 0.6–1.9, what is
the significance of the data? What conclusions can you draw about the “es campur”
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eating within the whole population? Give an example of a more significant OR and CI.
7. A doctor at puskesmas was function as program coordinator for transmitted disease at district with the total population was 500.000 persons. The result of surveillance for
several infectious diseases for 5 years was as follows: source UKDI
Diseases Year I
Year II Year III Year IV Year V
Malaria 30
35 32
34 31
DHF 0,6
0,5 0,4
0,9 2,1
Typhoid 5,1
5,4 4,8
6,2 5,8
Hepatitis C 2,1
2,2 1,8
1,7 1,6
Influenza 50
45 52
53 53
Which one of the above has become an outbreak?
a.
Malaria
b.
DHF
c.
Typhoid
d.
Hepatitis C
e.
Influenza
M O D U L E ~ 13
Greenberg
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Epidemiology Study to Determine Risk Factor of Disease
dr. Anak Agung Sagung Sawitri, MPH
Dr. dr. Gd Indraguna Pinatih, MSc., Sp.GK
AIMS:
1.
To describe the types and application of epidemiology study designs to determine risk factors of the disease of interest
2. To describe cross sectional longitudinal study design and to explain the advantages and disadvantages of cross sectional longitudinal study to determine risk factors of
diseases.
LEARNING OUTCOMES:
1. To describe and to draw types of epidemiology study designs and their applications 2. To describe advantages and weaknesses of epidemiology study designs
3. To describe and to draw cross sectional and longitudinal study design 4. To explain the advantages and disadvantages of cross sectional and longitudinal
study to determine risk factors of diseases 5. To explain what is prevalence ratio and how to calculate prevalence ratio in cross
sectional study 6. To explain the interpretation of prevalence ratio in cross sectional studies
7. To explain the incidence rate and how to calculate incidence in longitudinal study 8. To explain the interpretation of incidence rate in longitudinal studies
CURRICULUM CONTENTS:
1. Type, application and advantagesweaknesses of epidemiology study designs 2. The cross sectional and longitudinal study design and theirs attributes
3. Timing of measurements: cross sectional and longitudinal design 4. Data collection in cross sectional and longitudinal studies
5. Data analysis in cross sectional studies: prevalence ratio PR 6. Data analysis in longitudinal studies: incidence rate
ABSTRACTS
To prevent the disease, determinants or risk factors of the disease must be understood. To understand determinants or risk factors, epidemiological studies are
used. There are several epidemiological study designs those can be grouped into
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several ways. Based on the availability of intervention or not, the study designs can be divided into intervention or experimental study and observational study. Intervention
study is used to test the efficacy of treatment or prevention of certain disease in a population. Observational studies can be grouped into two groups based on whether
there are comparison groups or not. Descriptive study is an observational study without comparison group to study the distribution of the diseases occurrences in a population.
Analytic studies have comparison groups to study risk factors of diseases. Analytic studies can be defined into three based on the direction of the observation or the
measurement of the outcome. Cross-sectional is when the measurement or the observation of the disease under study outcome is at the same time with the
measurement of risk factors. Cohort design is prospective or effect to cause while case control design when the direction of the observation is retrospective or cause to effect.
Descriptive studies describe diseases occurrences “how much or how many” in the community based on “who”, “when” and “where” attributes. There are two major
purposes of this study, are for program planning and evaluation and for foundation of hypothesis testing of analytical studies experimental, cross-sectional, case-control and
cohort.
Each type of analytical study has advantages and disadvantages. Experimental study is not possible to be implemented in human when the aim is to study risk factors
cause of certain disease but It can be used to study treatment and prevention of certain disease. It is also the strongest design to test the hypotheses. Major disadvantage of
cross-sectional design is lack of temporal association since outcome disease and risk factors are measured at the same time. Major disadvantages of cohort design are
expensive and take long time especially when the disease incidence is low and the time between exposure and disease occurrence is long. Case-control design is less
expensive and faster than Cohort, however it has major weakness of information bias and difficult to match between “case group” and “control group”.
SELF DIRECTING LEARNING:
Basic knowledge and its application that students must know include: 1. Study design of cross sectional and longitudinal studies and their attributes
2. The procedures of cross sectional and longitudinal studies 3. Findings and its interpretation including crude PR, adjusted PR as well as
confounding factors in a cross sectional study 4. Findings and its interpretation including Crude and Specific Incidence Rate
SCENARIO LEARNING TASKS
Case 1. Please carefully study the article entitles: “Dengue and Other Common Causes of
Acute Febrile Illness in Asia: An Active Surveillance Study in Children”
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Learning Tasks 1:
After you carefully read through the article above, please discuss the following questions:
1. Draw a figure and explain the design of the study. Provide reasons for your
answer. 2.
What is the purpose of the study? 3.
What are the uses of this study? 4.
Does the study use primary or secondary data? a.
What is the source of the numerator? b.
What is the source of the denominator? 5.
Explain how researcher determines and selects the sample 6.
Explain how researcher measures the incidence of acute fever 7.
What are the three most common cause of fever in Asia? And what are the three most common cause of fever in Indonesia? What is the rank of Indonesia among
Asean countries in term of dengue? 8.
Explain the interpretation of incidence of dengue, chikungunya, and typhoid fever obtained from the study in Indonesia? The denominator is PY, what is the definition
and the strength of PY? 9.
Carefully observed Table 3. What measurements explained in the Table? Why researcher presenting that table?
10. How you interpret the 95 CI in the below data?
Case 2. Please carefully study the article entitles:“Bacterial vaginosis in female facility
workers in north-western Tanzania: prevalence and risk factors”
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Learning Tasks 2: After you carefully read through the article above, please discuss the
following questions:
1. What is the design of the study which investigated 1305 HSV-2 seropositive women aged 16-35 years and acyclovir 400mg? What is the dependent variable and
independent variable? Note: HSV: herpes simplex virus 2. What is the design of the study which investigated prevalence and risk factors for
bacterial vaginosis BV among HSV-2 seropositive women? What isare the dependent variable and independents variable?
3. Draw figures bagan of study designs. Firstly a figure of study to understand the outcome of acyclovir treatment toward HSV-2. Secondly a figure of study to find out
the association between BV and sex in the last week and other risk factors. Note: See Widagdo page 99 and page 148.
4. Calculate the 95 Confidence Interval of BV prevalence using the below formula and explain the interpretation.
Penghitungan CI untuk proporsi angka prevalens, angka insiden dan proporsi
CONTOH:
P proporsi kurang gizi = 23.2 N jumlah sampel = 400
RUMUS CI:
CATATAN:
Untuk nilai Z- nya yang dibagi 2 adalah alpha-nya.
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. 19
95 041
. 232
. 95
021 .
96 .
1 232
. 95
00044544 .
96 .
1 232
. 95
400 768
. 232
. 96
. 1
232 .
95 400
232 .
1 232
. 2
05 .
1 232
. 95
1
2 1
CI CI
X CI
CI CI
Z CI
n p
p z
p CI
82
Jadi untuk 95 CI, alpha nya berarti 5 di “Table Z” dicari nilai Z dari 1-α2 yaitu 1-0.025 atau nilai Z 0.975 yaitu 1.96
Kalau yang dicari adalah 99 CI dilihat di “Tabel Z” adalah nilai Z 0.995 yaitu 2.57
5. a List significant risk factors and their adjusted OR of BV which were found in this
