quality assurance -population and housing census alma kondi, instat, albania

Quality assurance -Population and Housing Census

Alma Kondi, INSTAT, Albania

National Institute of Statistics Albania

Contents

• Introduction• Measures taken to ensure quality data collection• Localization of errors and correction of the inconsistencies• The principles of data editing and imputation• Statistical evaluation- Deterministic corrections• Quality assessment indicators at aggregate level• Evaluation of the census quality based on Census/PES

matched records • Conclusion


Introduction

• Quality assurance is relevant for each activity and each operations stage of statistical operations.

• The main objective of this quality assurance is to provide valuable information for producer and the user of the data regarding the quality of census data.


Measures taken to ensure quality data collection

• Organizational measures- Trainings and training modules were given particular importance.

• Census data collection forms- The highest care was taken to ensure that questions were well understood

• Census mapping- An innovation of the Housing and Population Census 2011, was the implementation of GIS technology in all phases of census process.


Localization of errors and correction of the inconsistencies

• A number of processes were performed to turn the tick and text responses on the questionnaire into data that could be edited and imputed.

• Hear is summarizes the data processing adopted for the 2011 Albanian PHC:


The principles of data editing and imputation

• Editing- which consists in localize errors in collected data.

• Imputation of the localized errors and missing values: this second level of editing is also considered as the “correction” step of the errors in the responses.


Statistical evaluation- Deterministic corrections

• Not valid values can be replaced through deterministic or probabilistic corrections.

• A deterministic correction is generated by a constrain which if violated, lead to an error we are clearly able to correct.


Quality assessment indicators at aggregate level

Individual dataset Household dataset Dwelling dataset

Number of Records 2,800,138 722,262 1,021,332

Number of Variables 66 30 9

Number of Total values 184,809,108 21,667,860 9,191,988

Number of Valid values 180,558,499 21,376,712 9,003,207

Number of Valid blanks 79,399,119 13,568,117 1,334,076

Number of Valid non-blanks 101,159,380 7,808,595 7,669,131

Number of Imputed values 4,250,609 291,148 188,781

Number of Additions 2,180,747 236,641 117,126

Number of Eliminations 1,201,259 49,588 7,272

Number of Modification 868,603 4,919 64,383

Imputation rate (I) 2.3 1.3 2.1

Additions rate (Ia) 1.2 1.1 1.3

Elimination rate (Ie) 0.6 0.2 0.1

Modification rate (Im) 0.5 0.0 0.7

Non-Imputation rate 97.7 98.7 98.0

% of records with I greater than 2.0 30.9 16.0 14.2

% of records with I greater than 5.0 11.5 5.2 14.2


Evaluation of the census quality based on Census/PES matched records

• Even though the word ‘Census’ implies a 100 per cent count of the people and housing, it is rarely possible to achieve this.

• The Conference of European Statisticians (CES) agreed in their preparations for the 2010 and 2011 Censuses in Europe that the Censuses should be evaluated to check on coverage and the quality of the information provided.

• Further the European legislation on the censuses requires Member States to report on the quality of the census results that they transmit to the European Commission. Consideration should be given to coverage and quality of information collected in the Census


Statistical evaluation- Census/PES matched records

• It should be underlined that not all the difference between Census and PES data should be automatically considered as a mistake since both the Census and PES operations are affected by errors.

% 95% Confidence IntervalSex Lower Upper Different 1.3 0.4 2.1Equal 98.7 97.9 99.6Civil Status Different 3.8 1 5.9Equal 96.2 94.1 99 Age Different 6.9 1.4 9.8Equal 93.1 90.2 98.6


Statistical evaluation- Census/PES matched records

On the other hand PES was a smaller operation, the questionnaires were much easier and the enumerators were better trained. In this view, a conservative approach could be the assumption that each four differences three can be attributed to mistakes in the Census and only one to mistake in the PES.

TE TQ

Sex 1.0 99.0

Civil Status 2.8 97.2

Age 5.2 94.8


Conclusion

• A set of measures have been developed and introduced by INSTAT in order to guarantee the quality of the most important phase of the census: gathering complete and trustful data by all Albanian inhabitants.

• The overall procedure of edit and imputation of the 2011 Population and Housing Census in Albania is a very complex one.

• Impact of the edit and imputation procedure on the data related to the different units has been in some cases relevant, in order to obtain final datasets that are complete and free from inconsistencies and, at the same time, the original distributions have been preserved.

National Institute of Statistics Albania 13

Question Please?

Thank You

quality assurance -population and housing census alma kondi, instat, albania

Documents