6. Accuracy and reliability |
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6.1. Accuracy - overall |
6.1.1 How good is the accuracy? |
Good |
6.1.2 What are the main factors lowering the accuracy? |
Coverage error Non-response error Model assumption error |
6.1.3 If Other, please specify |
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6.1.4 Additional comments |
I tried to remove 'non-response error' in 6.1.2. but I couldn't do it. |
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6.2. Sampling error |
These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.2 of the annexed Excel file |
6.2.1 Name/Title |
Sample survey on Crop production |
6.2.2 Methods used to assess the sampling error |
Relative standard error |
6.2.3 If Other, please specify |
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6.2.4 Methods used to derive the extrapolation factor |
Basic weight Non-response |
6.2.5 If Other, please specify |
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6.2.6 If coefficients of variation are calculated, please describe the calculation methods and formulas |
The results were estimated with SAS software. Variances were estimated using the CLAN-macro developed by Statistics Sweden. |
6.2.7 Sampling error - indicators |
Please provide the coefficients of variation in table 6.2 of the annexed Excel file |
6.2.8 Additional comments |
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6.3. Non-sampling error |
See sections below. |
6.3.1. Coverage error |
Census
These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file |
6.3.1.1 Name/Title |
Statistics on cereals purchased, used and stockpiled by industry and trade |
Over-coverage |
6.3.1.2 Does the sample frame include wrongly classified units that are out of scope? |
No |
6.3.1.3 What methods are used to detect the out-of scope units? |
The business register is used as a frame, and the register is updated every year |
6.3.1.4 Does the sample frame include units that do not exist in practice? |
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6.3.1.5 Over-coverage - rate |
There is no over- coverage |
6.3.1.6 Impact on the data quality |
None |
Under-coverage |
6.3.1.7 Does the sample frame include all units falling within the scope of this survey? |
Yes |
6.3.1.8 If Not, which units are not included? |
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6.3.1.9 How large do you estimate the proportion of those units? (%) |
[0-100] |
6.3.1.10 Impact on the data quality |
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Misclassification |
6.3.1.11 Impact on the data quality |
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Common units |
6.3.1.12 Common units - proportion |
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6.3.1.13 Additional comments |
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Sample survey
These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file |
6.3.1.14 Name/Title |
Sample survey on Crop production |
Over-coverage |
6.3.1.15 Does the sample frame include wrongly classified units that are out of scope? |
Yes |
6.3.1.16 What methods are used to detect the out-of scope units? |
Farm may have fininshed the farm keeping after the sample has drawn |
6.3.1.17 Does the sample frame include units that do not exist in practice? |
No |
6.3.1.18 Over-coverage - rate |
1% |
6.3.1.19 Impact on the data quality |
None |
Under-coverage |
6.3.1.20 Does the sample frame include all units falling within the scope of this survey? |
Yes |
6.3.1.21 If Not, which units are not included? |
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6.3.1.22 How large do you estimate the proportion of those units? (%) |
[0-100] |
6.3.1.23 Impact on the data quality |
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Misclassification |
6.3.1.24 Impact on the data quality |
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Common units |
6.3.1.25 Common units - proportion |
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6.3.1.26 Additional comments |
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Administrative data
These questions only apply to administrative sources. If there is more than one administrative source, please describe the main source below and the additional ones in table 6.3 of the annexed Excel file |
6.3.1.27 Name/Title of the administrative source |
IACS - number of animals, cultivated area of crops |
Over-coverage |
6.3.1.28 Does the administrative source include wrongly classified units that are out of scope? |
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6.3.1.29 What methods are used to detect the out-of scope units? |
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6.3.1.30 Does the administrative source include units that do not exist in practice? |
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6.3.1.31 Over-coverage - rate |
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6.3.1.32 Impact on the data quality |
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Under-coverage |
6.3.1.33 Does the administrative source include all units falling within the scope of this survey? |
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6.3.1.34 If Not, which units are not included? |
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6.3.1.35 How large do you estimate the proportion of those units? (%) |
[0-100] |
6.3.1.36 Impact on the data quality |
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Misclassification |
6.3.1.37 Impact on the data quality |
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6.3.1.38 Additional comments |
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6.3.2. Measurement error |
Census
These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file |
6.3.2.1 Name/Title |
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6.3.2.2 Is the questionnaire based on usual concepts for respondents? |
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6.3.2.3 Number of censuses already performed with the current questionnaire? |
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6.3.2.4 Preparatory testing of the questionnaire? |
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6.3.2.5 Number of units participating in the tests? |
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6.3.2.6 Explanatory notes/handbook for surveyors/respondents? |
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6.3.2.7 On-line FAQ or Hot-line support for surveyors/respondents? |
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6.3.2.8 Are there pre-filled questions? |
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6.3.2.9 Percentage of pre-filled questions out of total number of questions |
[0-100] |
6.3.2.10 Other actions taken for reducing the measurement error? |
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6.3.2.11 Additional comments |
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Sample survey
These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file |
6.3.2.12 Name/Title |
Sample survey on crop production |
6.3.2.13 Is the questionnaire based on usual concepts for respondents? |
Yes |
6.3.2.14 Number of surveys already performed with the current questionnaire? |
26 |
6.3.2.15 Preparatory testing of the questionnaire? |
No |
6.3.2.16 Number of units participating in the tests? |
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6.3.2.17 Explanatory notes/handbook for surveyors/respondents? |
Yes |
6.3.2.18 On-line FAQ or Hot-line support for surveyors/respondents? |
Yes |
6.3.2.19 Are there pre-filled questions? |
Yes |
6.3.2.20 Percentage of pre-filled questions out of total number of questions |
16,6 % |
6.3.2.21 Other actions taken for reducing the measurement error? |
WEB- and CATI -survey included logical checks and min/max -checks - above actions improved the quality of data (e.g. no outliers or extraordinary values) |
6.3.2.22 Additional comments |
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6.3.3. Non response error |
Census
These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file |
6.3.3.1 Name/Title of the survey |
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6.3.3.2 Unit non-response - rate |
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6.3.3.3 How do you evaluate the recorded unit non-response rate in the overall context? |
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6.3.3.4 Measures taken for minimising the unit non-response |
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6.3.3.5 If Other, please specify |
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6.3.3.6 Item non-response rate |
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6.3.3.7 Item non-response rate - Minimum |
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6.3.3.8 Item non-response rate - Maximum |
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6.3.3.9 Which items had a high item non-response rate? |
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6.3.3.10 Additional comments |
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Sample survey
These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file |
6.3.3.11 Name/Title of the survey |
Sample survey on crop production |
6.3.3.12 Unit non-response - rate |
15 % |
6.3.3.13 How do you evaluate the recorded unit non-response rate in the overall context? |
Low |
6.3.3.14 Measures taken for minimising the unit non-response |
Reminders |
6.3.3.15 If Other, please specify |
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6.3.3.16 Item non-response rate |
Non existent - Due the controls and checks in WEB- and CATI -survey, the rate was non-existent. |
6.3.3.17 Item non-response rate - Minimum |
See 6.3.3.16 |
6.3.3.18 Item non-response rate - Maximum |
See 6.3.3.16 |
6.3.3.19 Which items had a high item non-response rate? |
See 6.3.3.16 |
6.3.3.20 Additional comments |
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6.3.4. Processing error |
Census
These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file |
6.3.4.1 Name/Title |
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6.3.4.2 Imputation - rate |
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6.3.4.3 Imputation - basis |
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6.3.4.4 If Other, please specify |
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6.3.4.5 Additional comments |
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Sample survey
These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file |
6.3.4.6 Name/Title |
Sample survey on crop statistics |
6.3.4.7 Imputation - rate |
Imputation is not used |
6.3.4.8 Imputation - basis |
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6.3.4.9 If Other, please specify |
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6.3.4.10 How do you evaluate the impact of imputation on Coefficients of Variation? |
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6.3.4.11 Additional comments |
There were numerous controls and checks during the survey (WEB- and CATI -based survey).Checks and controls resulted in either a warning or an error notification (=error). Due this controls and checks data processing errors are extremely unlike. |
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6.3.5. Model assumption error |
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6.4. Seasonal adjustment |
Not applicaple |
6.5. Data revision - policy |
Revision policy follows the national guidelines for Official Statistis of Finland (FOS). The OSF quality criteria are compatible with the quality criteria of the European Statistical System (ESS). |
6.6. Data revision - practice |
6.6.1 Data revision - average size |
One year |
6.6.2 Were data revisions due to conceptual changes (e.g. new definitions) carried out since the last quality report? |
No |
6.6.3 What was the main reason for the revisions? |
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6.6.4 How do you evaluate the impact of the revisions? |
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6.6.5 Additional comments |
Not yet known - new data production |
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