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IGNOU PGDAST MSTE 4 2024 Solution

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Last Date of Submission of IGNOU MSTE-04 (PGDAST) 2024 Assignment is for January 2024 Session: 30th September, 2024 (for December 2024 Term End Exam).
Semester Wise
January 2024 Session: 30th March, 2024 (for June 2024 Term End Exam).
July 2024 Session: 30th September, 2024 (for December 2024 Term End Exam).

Title Name	IGNOU MSTE 4 Biostatistics-II Solved Assignment 2024
Type	Soft Copy (E-Assignment) .pdf
University	IGNOU
Degree	PG DIPLOMA PROGRAMMES
Course Code	PGDAST
Course Name	Post Graduate Diploma in Applied Statistics
Subject Code	MSTE 4
Subject Name	Biostatistics-II
Year	2024
Session	-
Language	English Medium
Assignment Code	MSTE-04/Assignmentt-1//2024
Product Description	Assignment of PGDAST (Post Graduate Diploma in Applied Statistics) 2024. Latest MSTE 04 2024 Solved Assignment Solutions
Last Date of IGNOU Assignment Submission	Last Date of Submission of IGNOU MSTE-04 (PGDAST) 2024 Assignment is for January 2024 Session: 30th September, 2024 (for December 2024 Term End Exam). Semester Wise January 2024 Session: 30th March, 2024 (for June 2024 Term End Exam). July 2024 Session: 30th September, 2024 (for December 2024 Term End Exam).
Assignment Code	MSTE 4/2024

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Questions Included in this Help Book

Ques 1.

State whether the following statements are True or False. Give reason in support of your answer:

(a) The value of sensitivity of the following results of a diagnostic test is 0.85.

Disease	Test result		Total
Disease	+	-	Total
Present	170	30	200
Absent	20	280	300

(b) For the following cohort study, the relative risk for the lung cancer among smokers is 3.5.

	Lung Cancer	No Lung Cancer	Totel
Smokers	100	1220	1320
Non-smokers	50	2260	2310

(c) The logit link function is log $\left [ -log(1-\pi ) \right ],$
(d) We define three indicator/dummy variables for a regressor variable with three categories.
(e) Left censoring occurs whenever the exact time of occurrence of an event is not known.

Ques 2.

Differentiate between Chi-square tests for association and homogeneity of proportions. Also mention the assumptions of these tests.

Ques 3.

A random sample of 250 patients was selected and their workout timing and diabetes status were recorded. The following table shows the workout timing and severity of diabetes:

Workout (in minutes)	Severity of diabetes status
Workout (in minutes)	Low	Moderate	High
0 −15	06	27	19
15 to 30	08	38	17
30 to 45	21	45	33
≥ 45	14	18	06

Test at 5% level of significance whether workout habit and diabetes are associated with to each other or not.

Ques 4.

Explain the assumptions underlying multiple linear regression model.

Ques 5.

Suppose a researcher wants to evaluate the effect of cholesterol on the blood pressure. The following data on serum cholesterol (in mg/dL) and systolic blood pressure (in mm/Hg) were obtained for 15 patients to explore the relationship between cholesterol and blood pressure:

S. No.	Cholesterol (mg/dL)	SBP (mm/Hg)
1	300	150
2	410	270
3	380	210
4	530	310
5	570	350
6	490	310
7	340	210
8	320	150
9	280	110
10	550	320
11	340	220
12	350	170
13	410	260
14	390	230
15	450	270

(i) Fit a linear regression model using the method of least squares.
(ii) Construct the normal probability plot for the data on serum cholesterol and systolic blood pressure.
(iii) Test the significance of the fitted regression model.

Ques 6.

Polytomous logistic models

Ques 7.

Poisson regression

Ques 8.

Kaplan and Meier method

Ques 9.

The following data on diagnosis of coronary heart disease (where 0 indicating absence and 1 indicating presence), serum cholesterol (in mg/dl), resting blood pressure (in mmHg) and weight (in kg) were obtained for 80 patients to explore the relationship of coronary heart disease with cholesterol and weight.

S. No.	Serum Cholesterol (mg/dl)	Weight (kg)	Number of Patients having CHD	Total Number of Patients
1	420	60	10	20
2	450	68	15	30
3	400	54	4	15
4	510	74	2	10
5	480	62	1	5

(i) Fit a multiple logistic model for the dependence of coronary heart disease on the average serum cholesterol and weight considering
$\hat{\beta }_{0}^{0}=4.279,\hat{\beta }_{1}^{0}=-0.035$ and $\hat{\beta }_{2}^{0}=0.172$ the initial values of the parameters (solve only for one Iteration).
(ii) Test the significance of the fitted model using Hosmer-Lemeshow test at 5% level of significance.