Stata User Group Meeting 2017 – Canberra

28 September 2017

Speaker Presentations (sorted in last name alphabetical order)
Allan Barger, Department of Finance and Alastair Parker, Digital Transformation Agency data.gov.au and NationalMap - What's up with that
In December 2015 the Australian Government released its Public Data Policy Statement which required agencies to make open data discoverable through the data.gov.au platform. Since the release of the Statement the amount of open data discoverable through the platform has increased considerably. In this presentation we’ll introduce you to the data.gov.au and NationalMap platforms and share some tips and tricks about using them. We’ll cover things like searching for data, the data.gov.au API and NationalMap’s ability to turn tables into spatial data. Prepare to be pretty hands on. In June 2016 we started working with Data61 to create the next generation of the data.gov.au platform. To conclude we’ll talk about the work we’ve done to date and introduce you to our prototypes and design concepts showcasing what the future of data.gov.au could look like.

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Joe Hirschberg, The University of Melbourne A graphic comparison of the Fieller and Delta intervals for ratios of parameter estimates
Fieller’s 1954 proposal for the use of an inverse test to construct confidence intervals (Cis) for the ratio of normally distributed statistics has been shown to be superior to the application of the Delta method in a number of applications. In this presentation we demonstrate how a simple graphic exposition can be used to illustrate the relationship between the Delta and the Fieller Cis. The advantage of the graphical presentation over the numeric result available in the Fieller Stata ado (Coveney 2004) is that it may indicate how the level of significance can be changed to result in finite upper and lower bounds. In addition, we also demonstrate how this method can be used to draw inferences for the turning points in high order and fractile polynomials by the definition of the implied CIs for the first derivative function. A number of examples are provided in the area of the structural coefficient in the exactly identified two-stage Least squares estimator, the inflexion point in an environmental Kuznets curve and the 50% dose in a dose response model. There is a website for the programs and data that used in the slides - https://www.online.fbe.unimelb.edu.au/t_drive/stata_examples. These examples can all be shown with a simple Stata do file for the plots of a series of generated values.

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Paul Mwebaze, CSIRO Modelling technology adoption decisions among smallholder cassava producers in East Africa
Cassava is the second most important food crop in Africa after maize. It is a major staple crop for more than 200 million people in East and Central Africa. Recently, cassava has gained importance as a cash crop for smallholder farmers in this region. However, its production is constrained by several factors, particularly the lack of improved varieties resistant to emerging pests and diseases. Other constraints include socio-economic, environmental and institutional factors. We conducted a comprehensive socio-economic study covering Uganda, Tanzania and Malawi to determine the status of cassava production with the following specific objectives: (1) What is the present status of cassava production and productivity in these countries? (2) What is the current adoption rate of improved cassava production technologies? The primary data for this study was collected from cassava farmers—using a pre-tested survey questionnaire that was orally administered to individual farmers. A total of 1200 respondents were selected and interviewed using a multi-stage random sampling technique. Using the ‘mvprobit’ routine in Stata, we employ a multivariate probit regression to model simultaneous adoption of interrelated technology by smallholder cassava farmers. Here I present preliminary results and discuss the implications.

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Gwin Nyakuengama, Independent Advisor Stata is a key strategic statistical tool-of-choice in major impact evaluations of socio-economic programs
This presentation:
  • Outlines the program-logic of any major international impact program evaluation;
  • Discusses strategic considerations in such quantitative and qualitative evaluations, particularly the key attributes of a strategic data analytical tool;
  • Finds that STATA is internationally a highly regarded, state-of-the-art, swiss-knife used in data analysis of impact evaluations of social-economic programs.


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Francesca Orsini, Murdoch Children's Research Institute Standardised categorisation of maternal alcohol consumption throughout pregnancy
The AQUA (Asking Questions about Alcohol in Pregnancy) study assesses the impact of alcohol consumption on the unborn child. Data have been collected on nearly 1,600 pregnant women across four waves: the three months pre-pregnancy and at each trimester of pregnancy. The quantity and frequency of alcohol consumption for each woman and wave were collapsed into one of four categories (none, low, moderate or high), representing her average weekly alcohol consumption. A single occasion where 50 grams or more of alcohol were consumed was defined as a binge episode. Both average weekly consumption and number of binge episodes are taken into account in my analysis. The same survey questions on alcohol consumption were asked at each wave. I will present a standardised system for coding these questions and also the algorithm that calculates a woman's overall level of alcohol consumption at each wave. My ado-file can be adapted to other surveys aiming to quantify alcohol consumption.
Hua Peng, StataCorp Part of reproducible research is eliminating manual steps such as having to edit documents. Stata 15 introduces several commands that facilitate automated document production, including dyndoc for converting dynamic Markdown documents to webpages, putdocx for creating Word documents, and putpdf for creating PDF files. These commands allow you to mix formatted text and Stata output and allow you to embed Stata graphs, in-line Stata results, and tables containing the output from selected Stata commands. We will show these commands in action, demonstrating how to automate the production of documents in various formats and how to include Stata results in those documents.


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Bill Rising, StataCorp What's new in Stata 15
A brief overview of the new features of Stata 15. I will be discussing the newest features in what StataCorp President, Bill Gould, calls "our most remarkable release yet."
Joanna Sikora, Australian National University Adolescent interest in science careers in Europe: Trends between 2006 and 2015: example of Stata analysis
In this project we investigate trends in youth vocational interests related to STEM (science, technology, engineering and mathematics) in the OECD’s Programme for International Student Assessment data pooled for 2006 and 2015 data from 26 European countries. The focus is on ascertaining whether EU member states have succeeded in maintaining (or increasing) students’ interest in STEM careers in the decade and on exploring whether gender segregation within career expectations related to STEM has changed over time and across the EU countries. The data we use represent the so-called Large-Scale Assessment Studies and the presentation will focus mainly on the challenges of effective visual presentation of key results using Stata.

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Suzanna Vidmar, Murdoch Children's Research Institute Extracting metadata from Stata datasets
Data processed using Stata are often stored in proprietary Stata (*.dta) files. This is practical and useful for the life of a project but creates an obstacle for anyone who wishes to use the data, but who doesn't have Stata. The Stata command export writes data from a Stata dataset to a text file, a format that ensures portability and long term accessibility. However, the variable-level information in Stata data files, such as data types, variable labels and value labels, is lost. Ideally these metadata would also be extracted into a text file for long term preservation. In addition, the metadata could be imported into data capture software such as REDCap. My presentation will introduce an ado program that extracts variable-level metadata in a CSV format and illustrate how easily the metadata can be used to create either an empty or populated REDCap database.

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