Statistical validity

Compare with other Characteristic

Characteristic Name:	Statistical validity
Definition:	Computed data must be statistically valid
Dimension:	Validity
Granularity:	Information object
Characteristic Type:	Usage
Implementation Form:	Process-based approach

Verification Metric:

The number of tasks failed or under performed due to lack of statistical validity in data

The number of complaints received due to lack of statistical validity of data

Validation Metric:

To what extent required capabilities and skills have been implemented to improve the data usage of a task

BackgroundGuidelines

The original definitions given below formed the basis of the consolidated definition of the characteristic.

Definition:	Source:
Coherence of data refers to the internal consistency of the data. Coherence can be evaluated by determining if there is coherence between different data items for the same point in time, coherence between the same data items for different points in time or coherence between organisations or internationally. Coherence is promoted through the use of standard data concepts, classifications and target populations.	HIQA 2011. International Review of Data Quality Health Information and Quality Authority (HIQA), Ireland. http://www.hiqa.ie/press-release/2011-04-28-international-review-data-quality. More from this source
1) Accuracy in the general statistical sense denotes the closeness of computations or estimates to the exact or true values. 2) Coherence of statistics is their adequacy to be reliably combined in different ways and for various uses.	LYON, M. 2008. Assessing Data Quality , Monetary and Financial Statistics. Bank of England. http://www.bankofengland.co.uk/ statistics/Documents/ms/articles/art1mar08.pdf. More from this source

Definition:

Source:

Coherence of data refers to the internal consistency of the data. Coherence can be evaluated by determining if there is coherence between different data items for the same point in time, coherence between the same data items for different points in time or coherence between organisations or internationally. Coherence is promoted through the use of standard data concepts, classifications and target populations.

HIQA 2011. International Review of Data Quality Health Information and Quality Authority (HIQA), Ireland. http://www.hiqa.ie/press-release/2011-04-28-international-review-data-quality. More from this source

1) Accuracy in the general statistical sense denotes the closeness of computations or estimates to the exact or true values.

2) Coherence of statistics is their adequacy to be reliably combined in different ways and for various uses.

LYON, M. 2008. Assessing Data Quality ,
Monetary and Financial Statistics.
Bank of England. http://www.bankofengland.co.uk/
statistics/Documents/ms/articles/art1mar08.pdf. More from this source

The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation

Guidelines:	Scenario:
Establish the population of interest unambiguously with appropriate justification (maintain documentation)	(1) Both credit customers and cash customers are considered for a survey on customer satisfaction.
Establish an appropriate sampling method with appropriate justification	(1) Stratified sampling is used to investigate drug preference of the medical officers
Establish statistical validity of samples -avoid over coverage and under coverage (maintain documentation)	(1) Samples are taken from all income levels in a survey on vaccination
Maintain consistency of samples in case longitudinal analysis is performed. (Maintain documentation)	(1) Same population is used over the time to collect epidemic data for a longitudinal analysis
Ensure that valid statistical methods are used to enable valid inferences about data, valid comparisons of parameters and generalise the findings.	(1) Poisson distribution is used to make inferences since data generating events are occurred in a fixed interval of time and/or space
Ensure that the acceptable variations for estimated parameters are established with appropriate justifications	(1) 95% confidence interval is used in estimating the mean value
Ensure that appropriate imputation measures are taken to nullify the impact of problems relating to outliers, data collection and data collection procedures and the edit rules are defined and maintained.	(1) Incomplete responses are removed from the final data sample

Statistical validity

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