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ADRCE

ADRCE

Combining data from multiple administrative and survey sources for statistical purposes

Combining Data from Multiple Admin and Survey Sources for Statistical Purposes

Course Summary

Day one provides a general introduction to combining multiple administrative and survey datasets for statistical purposes. A total-error framework is presented for integrated statistical data, which provides a systematic overview of the origin and nature of the various potential errors. The most typical data configurations are illustrated and the relevant statistical methods reviewed.

Day two covers a handful of selected statistical methods. Training will be given on the techniques of data fusion, or statistical matching, by which joint statistical data is created from separate marginal observations. The participants will be introduced to several imputation or adjustment techniques, in the presence of constraints arising from overlapping data sources.

Target Audience:

This course is ideal for social and medical researchers with interests in combining data from multiple sources or analysing data from different sources; staff at National Statistical Institutes (or similar organisations) who are involved in the design, management and quality assurance of statistical processes based on data from multiple sources including censuses, administrative data and sample surveys.

 Pre-requisites:

Understanding of the following are required: central concepts of statistical uncertainty (such as bias, variance, confidence interval) and distribution, basic knowledge of data cleaning and imputation, basic experience/skill of R for statistical computing. Methodological training, knowledge and experience will be helpful.

Further course details can be found here.

Podcast for some of our previous courses can be found here

StartEndPlaces LeftCourse Fee 
07/11/201708/11/2017[Read More]
ADRCE

Confident Spatial Analysis

We are pleased to offer you this short course jointly organised by the Administrative Data Research Centre for England (ADRC-E) and the Consumer Data Research Centre (CDRC).

In this course we will cover how to prepare and analyse spatial data in RStudio & GeoDa. We will use RStudio to perform spatial overlay techniques (such as union, intersection and buffers) to combine different spatial data layers to support a spatial analysis decision. We will also use RStudio and GeoDa to explore a range of different spatial analyses including Moran’s I and clustering. By the end of the course you will understand how RStudio manages spatial data and be able to use RStudio for a range of spatial analysis.

If you are not already familiar with the basic elements of GIS or R, you may wish to attend the one-day course ‘Introduction to Spatial Data & Using R as a GIS’ prior to this course on 20 July where these skills are covered.

 

Further course details can be found here.

 

More information regarding our courses can be found here.

 

Podcast for some of our previous courses can be found here.

 

StartEndPlaces LeftCourse Fee 
21/07/201721/07/2017[Read More]
Generating Synthetic Data for Statistical Disclosure Control

Generating Synthetic Data for Statistical Disclosure Control

Course Summary

This short course will provide a detailed overview of the topic, covering all important aspects relevant for the synthetic data approach. Starting with a short introduction to data confidentiality in general and synthetic data in particular, the workshop will discuss the different approaches to generating synthetic datasets in detail. Possible modelling strategies and analytical validity evaluations will be assessed and potential measures to quantify the remaining risk of disclosure will be presented.

The aim is to provide the participants with hands on experience, the course will include practical sessions using R, in which the students generate and evaluate synthetic data based on real data examples.

Target Audience

The course intends to summarize the state of the art in synthetic data. The main focus will be on practical implementation and not so much on the motivation of the underlying statistical theory. Participants may be academic researchers or practitioners from statistical agencies working in the area of data confidentiality and data access. Basic knowledge in R is expected. Some background in Bayesian statistics is helpful but not obligatory.

Further information can be found here

 

More information regarding our courses can be found here.

 

Podcast for some of our previous courses can be found here.

StartEndPlaces LeftCourse Fee 
16/10/201717/10/2017[Read More]
Introduction to Data Linkage

Introduction to Data Linkage

This short course is designed to give participants a practical introduction to data linkage and is aimed at researchers either intending to use data linkage themselves or to analyse linked data. Examples of the uses of data linkage, data preparation, methods for linkage (including deterministic and probabilistic approaches) and issues for the analysis of linked data are covered. The main focus of this course will be health data, although the concepts will apply to many other areas. This course includes a practical example involving data to be linked, to enable participants to put theory into practice.  

Target Audience

The course is aimed at researchers who need to gain an understanding of data linkage techniques. The course provides an introduction to data linkage theory and methods for those who might be using linked data in their own work. Participants may be academic researchers in the social and health sciences or may work in government, survey agencies, official statistics, for charities or the private sector.

 

Further course details can be found here.

 

More information regarding our courses can be found here.

 

Podcast for some of our previous courses can be found here.

StartEndPlaces LeftCourse Fee 
05/09/201705/09/2017[Read More]
ADRCE & CDRC logo

Introduction to Hospital Episode Statistics

This course will provide participants with an understanding of how Hospital Episode Statistics (HES) data are collected and coded, their structure, and how to clean and analyse HES data. A key focus will be on developing an understanding of the strengths and weaknesses of HES data, how inconsistencies arise, and approaches to deal with these. Participants will also learn how to ensure individuals’ anonymity and confidentiality when analysing and publishing using HES. The course consists of a mixture of lectures and practicals for which participants will use Stata software to clean and analyse HES data.

 

Target Audience

Researchers at all levels in academia, government and private sector at all levels who are using/planning to use Hospital Episode Statistics in their work.

 

Further course details can be found here.

 

More information regarding our courses can be found here.

 

Podcast for some of our previous courses can be found here.

StartEndPlaces LeftCourse Fee 
18/09/201719/09/2017[Read More]
ADRCE logos

Introduction to QGIS: Understanding and Presenting Spatial Data

We are pleased to offer you this short course jointly organised by the Administrative Data Research Centre for England (ADRC-E) and Consumer Data Research Centre (CDRC).

Please note this course can be taken as a one-day course, or can also be taken in conjunction with other two one-day courses on 20 July and 21 July 2017.

This course will introduce spatial data and show you how to import and display spatial data with the free open source GIS program QGIS. We will also show you how to create choropleth maps and explain appropriate methods of visualising spatial data. We will also cover some basic spatial data analysis (e.g. calculating rates).

 

This course is ideal for anyone who wishes to use spatial data in their role. This includes academics, commercial users, government & other public sector researchers who have data with some spatial information (e.g. address, postcode, etc.) which they wish to show on a map. This course is also suitable for those who wish to have an overview of what spatial data can be used for. No previous experience of spatial data is required.

 

No previous experience of GIS or QGIS is required, but some experience of using spatial data will be beneficial.

 

Further course details can be found here.

 

More information regarding our courses can be found here.

 

Podcast for some of our previous courses can be found here.

StartEndPlaces LeftCourse Fee 
19/07/201719/07/2017[Read More]
ADRCE

Introduction to Spatial Data & Using R as a GIS

We are pleased to offer you this short course jointly organised by the Administrative Data Research Centre for England (ADRC-E) and the Consumer Data Research Centre (CDRC).

Please note this course can be taken as a one-day course, or can also be taken in conjunction with other two one-day courses on 19 July and 21 July 2017.

The course will cover an introduction to R, how to load and manage spatial data and how to create maps using R and RStudio. We will show you appropriate ways of using classifications for choropleth maps, using loops in R to create multiple maps and some basic spatial analysis.

We will be using RStudio to work with the R environment. By the end of the course you will be able to load data into R, represent it effectively and be able to prepare an output quality map.

 

This course is ideal for anyone who wishes to use spatial data in their role. This includes academics, commercial users, government & other public sector researchers who have data with some spatial information (e.g. address, postcode, etc.) which they wish to show on a map. This course is also suitable for those who wish to have an overview of what spatial data can be used for. No previous experience of spatial data is required.

 

No experience of spatial data, GIS or scripting required. Some basic experience of using Google Earth / Maps would be beneficial.

 

 

Further course details can be found here.

 

More information regarding our courses can be found here.

 

Podcast for some of our previous courses can be found here.

StartEndPlaces LeftCourse Fee 
20/07/201720/07/2017[Read More]
adrce

SQL Database Management Software Edinburgh

Course Summary

Database systems are increasingly being used for working with medical data and enable the rapid querying of complex data in health and social care.

This short course will introduce the theory behind the relational data model and enable participants to gain an understanding on how data can be modelled and stored in a relational database system and what different data types are used.

Through a series of practical-driven sessions using real-life data, students will learn how to load existing data in a contemporary relational database management system and how to craft simple and complex queries for analysing the data. By the end of the course, students will be able to load, format and export data in a format suitable for analysis by common statistical packages.

Target Audience:

Course suitable for epidemiologists, medical statisticians and other researchers working with electronic health records data.

Further course details can be found here.

 

More information regarding our courses can be found here.

 

Podcast for some of our previous courses can be found here.

StartEndPlaces LeftCourse Fee 
30/01/201830/01/2018[Read More]

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