Week 3 assignment

Week 3 assignment

by Amy -
Number of replies: 1

World Management Survey (Schools 2008-2012)

A survey to collect management practices data from firms across different countries and industries. This dataset is specific to 1,800 high schools in eight countries (Brazil, Canada, Germany, India, Italy, Sweden, UK, and US). Data was collected through telephone interviews with school principles and includes questions about management practices related to: operations, monitoring, target setting and people. In addition, school level student outcomes were collected from examination results across regions and countries.

Strong RQ – How do school management practices differ between countries and between types of schools (government, private, charter, etc.)?

This sample includes data about schools from across multiple countries and types, and so it’s possible to describe the differences and even to understand whether the classification of a school impacts the management practices that are implemented to see if there is a relationship between the type and strength of management practices. 

Weak RQ – What school management practices are most important to better student outcomes?

Student outcomes are not consistently measured across countries. Similar to the comparison of HRS and ELSA data to ascertain differences in disease incidence and prevalence, the lack of consistency in data collection makes comparing results suspect.

 

Pew Research Center Gender and Leadership Survey (2014)

A survey of 1,835 randomly selected adults (921 women and 914 men) conducted online using a nationally representative online research panel recruited through probability sampling methods. The sample was weighted using a technique to match gender, and within gender, age, race, education, region, HH income, home ownership and metropolitan area to the parameters from the 2013 Current Population Survey.

Strong RQ – How have perceptions about equal leadership opportunities for women changed over time?

Data has been collected using this survey instrument since 2007 and so it is possible to explore trends over time in the aggregate.

Weak RQ – How do perceptions about equal leadership opportunities for women differ by respondent background (SES, geography, etc.)?

Given the relatively small sample size and reliance on weighting, it might not be as accurate to look at comparisons between sub-populations.

 

WHO/CDC Global Health Professional Survey (GHPS)

A survey developed in 2004 to collect data on tobacco use and cessation among health professional students because they are responsible for providing health care resulting from and education about tobacco use. The survey was conducted in 2005 among third year students pursuing advanced health science degrees in ten countries (Albania, Argentina, Bangladesh, Croatia, Egypt, Bosnia & Herzegovina, India, Philippines, Serbia, and Uganda).

Strong RQ – Is there a difference in the attitudes of smokers/non-smokers as to how health professionals should be trained about smoking cessation?

For the specific sub-populations studied in this survey, this question can be answered to provide some directional guidance. 

Weak RQ – How does tobacco use vary between different types of health professionals and the general population?

The survey did not include students from each type of health profession in each country and the sample sizes were not established or weighted to be representative of the population of health professional within country, so comparisons between these categories cannot be extrapolated to represent the population of health professionals of any type in any country. Data about prevalence of adult smoking in each country is not collected in a uniform manner and so comparisons are not appropriate. Furthermore, given that this survey was done among students, it is not clear that the same results would persist among practicing clinicians.

In reply to Amy

Re: Week 3 assignment

by Maria Glymour -

Amy,

These are great examples.  For the World Management Survey of Schools, were the schools selected w/ some type of probability sampling, and was the sample design comparable between countries?  This is a critical question for the type of cross-national comparison you propose because it rests on having a representative sample in each country. 

The issue of how to compare latent constructs, such as student performance, cognition, depression, disability, across cultural settings is a tremendous challenge.  HRS and ELSA were actually designed to ask parallel questions to facilitate harmonized analyses but we end up struggling still with differences in diagnosis rates, diagnostic criteria, etc.  This problem is even worse when you try to incorporate evidence from countries with different languages, different literacy levels etc.  There are a few approaches to harmonizing, e.g., line up "objective" and "subjective" measures, but these are remarkably inconsistent.  

Re the Pew study: there is a really important distinction between research questions that require you to characterize the prevalence of average value of a characteristic in the population (e.g. average blood pressure, or average attitudes about women in leadership) versus those that require you to characterize the association between two characteristics in a population (e.g., do women have different attitudes about female leadership than men?).  In general, the former type of question is harder to get right.  If any aspect of the Pew sampling strategy changed over time, for example, they broadened their recruitment approach, or they incorporated cell phones into their sample, or they improved their software so people with less computer savvy could successfully complete the survey, it could easily mess up the trend results.  On the other hand, if the question is about the association between two variables (say X and Y for brevity), this type of change in the selection process only matters if the association between X and Y is different for different types of people.   We should discuss more in class.  This has generated a bit debate in epidemiology re the importance of representative samples.