Create the mean summary measure

Assignment Help Applied Statistics

Reference no: EM132555466

The data consist of growth measurements for 11 girls and 16 boys at ages 8, 10, 12, and 14.

Part A

Based on the long form of this data set, considering the effect of gender, generate the following:
Individual response profile
Mean response profile
Boxplot response profile

Based on the wide form of this data set
Create the mean summary measure (MSM) of (y2 y3 y4)
Generate the boxplot for mean summary measure by gender
Perform an analysis of covariance
model MSM = y1 Gender
Repeat using y4 as a summary measure instead of MSM.

Fit a random intercept linear mixed effect model.
Produce a plot comparing the actual individual response profile to the predicted.
Repeat the above using a random slope and intercept model.
Give your conclusions about the above models.

Part B Data / Introduction

The purpose here is to understand the impact of different types of missing/dropout on the estimation results

The response is a continuous variable
Baseline measure at time 0
Repeated measures at time 1, 2, ..., 10

Two explanatory variables are associated with the response in the simulation model
Binary variable X
Continuous variable Z

Based on the originally simulated data, we generate the data set with different types of missing/dropout observations

Report

What have you observed/discovered from the analysis of different data sets?

Discuss briefly the impact of different types of missing/dropout on the estimation results

Part C

Based on the wide data form, explore the correlation among the responses at different time points
Based on the long data form, considering the effect of X, explore the following
Pooled individual response profiles
Mean response profiles
Boxplot response profiles

Build a GEE based GLM for the response vs. the following explanatory variables: X, Z, time
With independent working correlation structure
With AR working correlation structure
Build a GLIMMIX for the response vs. the following explanatory variables: X, Z, time
Consider a random effect for the Intercept
Summarize your results and indicate if the results are similar, or if one model is more appropriate than the other

Part D

Based on the wide data form, explore the association among the responses at different time points
Based on the long data form, considering the effect of X, explore the following
Pooled individual response profiles
Mean response profiles
Boxplot response profiles

Attachment:- Homework.rar

Reference no: EM132555466

Questions Cloud

Relationship between sickle cell anemia and malaria : What is the relationship between sickle cell anemia and malaria. Are there resistant strains of malaria? How are these treated?

Define how knowledge informed by data that is collected : Among the Resources in this module is the Rutherford (2008) article Standardized Nursing Language: What Does It Mean for Nursing Practice? In this article.

Strands of the dna molecule : Choose the true statement(s) about DNA replication. To be marked correct, you'll need to select all true statements, as there may be more than one correct answe

What can the nurse do to assess and integrate spirituality : What can the nurse do to assess and integrate spirituality into Victor's care? If the family is in another state what can the nurse do to integrate the family.

Create the mean summary measure : Part A (data/introduction) - impact of different types of missing/dropout on the estimation results and What have you observed/discovered from the analysis

Appearing in the national or international media : This assignment should be a brief analysis of a news report/article appearing in the national or international media.

Evaluate importance of implementing a fraud risk monitoring : Examine the environment in which Alibaba was operating that caused them to develop a fraud risk monitoring and management system.

Atomic composition of the major macromolecules : Describe the atomic composition of the major macromolecules: proteins, lipids, nucleic acids (DNA and RNA) and carbohydrates.

CIS1000 Information Systems Concepts Assignment : CIS1000 Information Systems Concepts Assignment Help and Solution - University of Southern Queensland, Australia - Assessment Writing Service

User Account

All Pages