Data should be available and easily accessible. The process of obtaining data can be lengthy, especially if data are classed as sensitive, for example on sexual identity. Analysis of change over time should be possible (so data are collected reasonably frequently), allowing for monitoring; it may be necessary to pool of data, for example for smaller samples such as when looking at Scotland or Wales, or when looking at some protected groups, such as ethnic minorities. Continuity should be provided, not only in the provision of data but in continuity of definitions (for example, of disability) or question wording (if data are survey-based). There should be good geographical coverage, preferably including Britain, England, Scotland and Wales, from one source. Failing that, country-specific data that is comparable is preferred, but not always available. In addition, data for the English Regions and/ or disaggregated into the Rural-Urban categories. It should be possible to disaggregate according to as many as possible of the nine protected characteristics set out in the Equality Act (age, disability, gender reassignment, race, religion or belief, sex, sexual orientation, pregnancy and maternity, marriage and partnership). Further, it should be possible to disaggregate disability data into categories of impairment type. Although it is not one of the protected characteristics, we also aim to socio-economic group/ social class, as it is a crucial characteristic that impacts upon life opportunities across all domains. Data should be subject to the standard statistical requirements of accuracy, reliability and validity. Statistical tests that are used to evaluate statistically significant differences for each measure depend on the form of the measure involved (percentage, mean, median, rate or count) and the underlying form of the dependent variable involved (binary, continuous or integer). Statistical analysis includes cross-sectional analysis for two or more time periods, with comparisons between groups in each time period, plus change over time within groups. Where suitable microdata are available from the data source, intersectional analysis will also be carried out using appropriate regression models using data on
Data should be available and easily accessible. The process of obtaining data can be lengthy, especially if data are classed as sensitive, for example on sexual identity. Analysis of change over time should be possible (so data are collected reasonably frequently), allowing for monitoring; it may be necessary to pool of data, for example for smaller samples such as when looking at Scotland or Wales, or when looking at some protected groups, such as ethnic minorities. Continuity should be provided, not only in the provision of data but in continuity of definitions (for example, of disability) or question wording (if data are survey-based). There should be good geographical coverage, preferably including Britain, England, Scotland and Wales, from one source. Failing that, country-specific data that is comparable is preferred, but not always available. In addition, data for the English Regions and/ or disaggregated into the Rural-Urban categories. It should be possible to disaggregate according to as many as possible of the nine protected characteristics set out in the Equality Act (age, disability, gender reassignment, race, religion or belief, sex, sexual orientation, pregnancy and maternity, marriage and partnership). Further, it should be possible to disaggregate disability data into categories of impairment type. Although it is not one of the protected characteristics, we also aim to socio-economic group/ social class, as it is a crucial characteristic that impacts upon life opportunities across all domains. Data should be subject to the standard statistical requirements of accuracy, reliability and validity. Statistical tests that are used to evaluate statistically significant differences for each measure depend on the form of the measure involved (percentage, mean, median, rate or count) and the underlying form of the dependent variable involved (binary, continuous or integer). Statistical analysis includes cross-sectional analysis for two or more time periods, with comparisons between groups in each time period, plus change over time within groups. Where suitable microdata are available from the data source, intersectional analysis will also be carried out using appropriate regression models using data on