This chapter reviews the methodology and quality of jurisdictional early childhood education and care data and the sources from which the data were collected for the 2012 National Early Childhood Education Care (ECEC) Collection. As there is considerable variability in the data collected by each of the jurisdictions, this chapter aims to clarify the quality of the data and the mechanisms used for collecting the data.
The ABS Data Quality Framework, May 2009 (cat. no 1520.0) has been used to evaluate the quality of each jurisdictional collection which contributes data to the National ECEC Collection.
Each jurisdictional collection has been assessed using an individual data quality statement, and as such the statements relate only to the quality and coverage of each individual jurisdictional collection as a separate entity. For example, in those state and territories where data for Long Day Care centres will be sourced from the Child Care Management System (CCMS), information concerning the quality assessment of the CCMS is not included.
The dimensions which make up the Data Quality Statements are defined as follows.
This dimension refers to the institutional and organisational factors which may have a significant influence on the effectiveness and credibility of the agency producing the statistics. This considers the surrounding context, which may influence the validity, reliability or appropriateness of the data. Information contained in this section includes the organisation responsible for collecting and compiling the data, and the authority or legislation under which the data were collected.
The assessment indicates how well the jurisdictional data source meets the needs of the National ECEC Collection in terms of the concepts measured, and the populations represented. This criterion also outlines the collection scope and coverage. Information provided includes the original purpose for collecting the data, the collection scope and population of interest for the data collected, and any coverage limitations.
Timeliness refers to the delay between the reference period (to which the data pertains) and the date on which the data become available. This includes the time taken for the jurisdiction to deliver the data to the ABS and the time taken for the ABS to release the data. It also refers to the frequency with which data are collected.
Data sources employ a range of methods to collect data. In this context accuracy refers to the degree with which the data correctly describe the phenomenon they were designed to measure. This is an important component of quality as it relates to how accurate the data are and impacts on how useful and meaningful the data will be for interpretation or further analysis. An assessment is made on the accessibility and availability of a source and the implications on statistics for the National ECEC Collection. To describe this dimension for the National ECEC Collection, information is provided on the collection mechanism, data processing and validation procedures.
Coherence refers to the internal consistency of a statistical collection, product or release, as well as its comparability with other sources of information, within a broad analytical framework and over time. The use of standard concepts, classifications and target populations promotes coherence, as does the use of common methodology across collections. Coherence is an important component of quality as it provides an indication of whether the data set can be usefully compared with other sources to enable data compilation and comparison. In the context of the National ECEC Collection this assessment also examines changes in concepts and alignment with the ECEC National Minimum Data Set.
Counts of Children:
This section also outlines whether jurisdictional data are able to be presented in terms of the following table concepts for the publication Preschool Education, Australia, 2012 (cat. no 4240.0):
- Children in a preschool program in 2012; and
- Children in a preschool program in the Year before Full-time Schooling.
The concept of child counts is discussed in more detail in Chapter 3, Concepts and Definitions
Interpretability refers to the availability of information to help provide insight into the data. Assisting with the interpretation of the data may include the variables used and the availability of metadata, including concepts, classifications, and measures of accuracy. This section outlines further information that is available to help users better understand the data source, as well as information made available to data providers to assist with the initial collection and collation of the data.
Accessibility refers to the ease of access to data by users, including the ease with which the existence of information can be ascertained, as well as the suitability of the form or medium through which information can be accessed. For the purpose of the data quality framework, data accessibility relates to the publication Preschool Education, Australia, 2012
. (cat. no 4240.0)
This section outlines the source of information used to compile the data quality statement.