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rmarkdown/Page_1_Homepage.rmd

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+---
+title: "Home"
+output:
+  html_document:
+    toc: yes
+    toc_depth: 4
+    toc_float:
+      collapsed: yes
+  pdf_document:
+    toc: yes
+    toc_depth: '4'
+---
+
+```{r global-options, include=FALSE}
+# Set echo=false for all chunks
+knitr::opts_chunk$set(echo=FALSE)
+```
+
+---
+
+## Background
+
+The Administrative Data Quality Question Bank (ADQQB) is a collection of specially designed questions that act as a guide to help analysts to understand the quality of their administrative data for research and statistical purposes. These questions can be used in two ways. 
+
+
+Analysts can ask the data suppliers these questions. It is strongly encouraged for analysts to communicate with data suppliers prior to undertaking any research using administrative data, to fully understand the data in question and its’ quality. 
+
+
+Analysts can also use these questions as their own guides when assessing the quality of their data.  
+
+ <br> 
+
+The questions have been designed to guide the analyst to do the following: 
+
++ understand the data at the point that either the analyst or organisation has acquired and accessed the administrative data  
+
++ make the right decisions on how to treat the data at the data processing and analysis phase and onwards 
+
++ determine whether the data are fit for purpose 
+
++ transparently communicate the quality of the data in statistical research and outputs 
+
+
+
+
+As such, this question bank falls within the requirements of the three principles of government statistical data Quality, as set out in the [Code of Practice for Statistics](https://code.statisticsauthority.gov.uk/): 
+
++ suitable data sources 
+
++ sound methods 
+
++ assured quality
+
+
+
+<br> 
+
+The question bank has also been designed to be consistent with, and is encouraged to be used alongside [the Administrative Data Quality Framework (ADQF)](https://analysisfunction.civilservice.gov.uk/policy-store/quality-of-administrative-data-in-statistics/). The question bank consists of:
+
++ an explanation of what it is and how it can be used 
+
++ examples of questions, organised by theme and sub-theme  
+
++ description of the themes the questions are organised into, including definitions where appropriate 
+
+
+
+
+<br>
+
+
+## What are administrative data in statistics and research? 
+
+
+Administrative data are data which have been collected during the operations of an organisation. Government produces a large amount of administrative data, which can provide a valuable resource in the production of statistics. Administrative data must be accessed securely and via legal gateways. Their use represents an opportunity for analysts, however, it is important to remember that the subjects of the data must be protected from misuse. This question bank does not support you with making decisions about access to data, however, this is something you need to consider. Your organisation will have data protection policies, such as [these data protection guidelines from the ONS](https://www.ons.gov.uk/aboutus/transparencyandgovernance/dataprotection). If you have questions, you should contact your Data Protection Officer.
+
+
+
+Administrative data are collected for operational purposes and not statistical purposes. This can lead to challenges when using it for statistics, a summary of which can be found in David Hand’s paper, [“Statistical challenges of administrative and transaction data”](https://rss.onlinelibrary.wiley.com/doi/10.1111/rssa.12315).  
+
+<br>

rmarkdown/Page_2_Question_Bank_Use.rmd

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+---
+title: "How to use the question bank"
+output:
+  html_document:
+    toc: yes
+    toc_depth: 4
+    toc_float:
+      collapsed: yes
+  pdf_document:
+    toc: yes
+    toc_depth: '4'
+---
+
+```{r global-options, include=FALSE}
+# Set echo=false for all chunks
+knitr::opts_chunk$set(echo=FALSE)
+```
+
+---
+
+## Question bank structure and how to use 
+
+
+This question bank groups questions into sections, some of which having further sub-sections. These sections and sub-sections are as follows: 
+
+
+
+1. Quality dimensions as defined by the Data Management Association UK (DAMA), paired into the following: 
+
+    * accuracy and validity 
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+    * completeness and uniqueness 
+
+    * consistency and timeliness 
+
+
+
+2. Data linkage 
+
+
+
+These sections and their sub-sections have been chosen to give you a wide selection of questions to gain further insights into administrative data quality. According to the [Code of Practice for Statistics](https://code.statisticsauthority.gov.uk/), “quality means that statistics fit their intended uses, are based on appropriate data and methods, and are not materially misleading.” 
+
+In essence, quality centers around a consideration of fitness for purpose, including: 
+
++ Are the data good enough for what I want to use it for? 
+
++ Did the statistic I produce meet the needs of the people who are using it?  
+
+<br>
+
+The questions in this question bank can be used to assess the different aspects of fitness for your use. Very rarely will there be data that is completely perfect for statistical and research purposes. Understanding which dimensions are important for your specific uses will help you when deciding if data are fit for purpose. To this end, the question bank has been designed to be flexible, and your approach can be tailored in proportion to your needs, for example, by making them relevant to the variables you are interested in. These questions provide a structure into assessing the data’s fitness for purpose and ensuring that you cover the key issues to help understand the data’s quality.  
+
+
+The first key step is to identify what dataset you are interested in and wish to assess using the set of questions in this question bank. You can then use the questions in this The Administrative Data Quality Question Bank (ADQQB) and tailor these to find out more about that specific dataset. 
+
+
+The Administrative Data Quality Question Bank (ADQQB) focuses on assessing quality of data at input data level. Input data level refers to the point at which your organisation receives the data. Quality at this stage refers to how well the data fits the purpose(s) you want to use them for. Essentially, this could be suitability of the data to produce statistics, or suitability of the data to carry out analysis or research. 
+
+<br>
+
+We have included questions on the [DAMA quality dimensions](https://www.gov.uk/government/news/meet-the-data-quality-dimensions) because these are dimensions that are widely used across the government to assess if data is good enough to use, or whether improvements need to be made. We have also chosen to include questions on data linkage in data collection and production as answers to these questions could supply further information and context around how the data are produced. It also provides a reminder that you should check-in regularly with the data suppliers regarding any changes that may affect the resulting data. 
+
+
+As we further develop the Administrative Data Quality Question Bank (ADQQB)  beyond the current publication, we will add further sections. These will include output data quality: "how well your ‘final’ output meets your users’ needs”. This will be done through integrating relevant dimensions from the European Statistical System’s (ESS) dimensions of quality. 
+
+
+<br>
+
+
+
+