Data Quality Reviews. As determined in the M&E Plan or as otherwise requested by MCC, the quality of the data gathered through the M&E Plan will be reviewed to ensure that data reported are as valid, reliable, and timely as resources will allow. The objective of any data quality review will be to verify the quality and the consistency of performance data across different implementation units and reporting institutions. Such data quality reviews also will serve to identify where those levels of quality are not possible, given the realities of data collection.
Data Quality Reviews. Data Quality Reviews (“DQR”) are a mechanism to review and analyze the utility, objectivity, and integrity of performance information. DQRs are to cover: a) quality of data; b) data collection instruments; c) survey sampling methodology; d) data collection procedures; e) data entry, storage, and retrieval processes; f) data manipulation and analyses; and g) data dissemination. MCC requires that an independent entity conduct the DQR, such as a local or international specialized firm or research organization, or an individual consultant, depending on the size of the Program or Project in review. The frequency and timing of data quality reviews must be set forth in the M&E Plan; however, MCC may request a DQR at any time. DQRs should be timed to occur before or early enough in the Compact Term that meaningful remedial measures (if any) may be taken depending on the results of the review. The methodology for the review should include a mix of document and record reviews, site visits, key informant interviews, and focus groups.
Data Quality Reviews. From time to time, as determined in the M&E Plan or as otherwise requested by MCC, the quality of the data gathered through the M&E Plan shall be reviewed to ensure that data reported are as valid, reliable, and timely as resources will allow. The objective of any data quality review will be to verify the quality and the consistency of performance data, across different implementation units and reporting institutions. Such data quality reviews also will serve to identify where those levels of quality are not possible, given the realities of data collection. The data quality reviewer shall enter into an Auditor / Reviewer Agreement with MCA-Georgia in accordance with Annex I.
Data Quality Reviews. Data Quality Reviews (“DQR”) are a mechanism to review and analyze the utility, objectivity, and integrity of performance information. DQRs are to cover: a) quality of data, b) data collection instruments, c) survey sampling methodology, d) data collection procedures, e) data entry, storage and retrieval processes, f) data manipulation and analyses and g) data dissemination. MCC requires that an independent entity conduct the DQR, such as a local or international specialized firm or research organization, or an individual consultant, depending on the size of the Program or Project in review. The frequency and timing of data quality reviews must be set forth in the M&E Plan; however MCC may request a DQR at any time. DQRs should be timed to occur before or early enough in the Compact Term that meaningful remedial measures (if any) may be taken depending on the results of the review. The methodology for the review should include a mix of document and record reviews, site visits, key informant interviews, and focus groups.
Data Quality Reviews. Data Quality Reviews (“DQR”) are a mechanism to review and analyze the utility, objectivity, and integrity of performance information. DQRs are to cover: (a) quality of data, (b) data collection instruments, (c) survey sampling methodology, (d) data collection procedures, (e) data entry, storage and retrieval processes, (f) data manipulation and analyses, and (g) data dissemination. MCC requires that an independent entity conduct the DQR, such as a local or international specialized firm or research organization, or an individual consultant, depending on the size of the program or project in review. The frequency and timing of data quality reviews must be set forth in the M&E Plan; however, MCC may request a DQR at any time. DQRs should be timed to occur before or early enough in the term of this Agreement that meaningful remedial measures (if any) may be taken depending on the results of the review. The methodology for the review should include a mix of document and record reviews, site visits, key informant interviews, and focus groups.
Data Quality Reviews. Data Quality Reviews (“DQR”) are a mechanism to review and analyze the quality and utility of performance information. They cover all data reported in the ITT, and all primary sources that feed into that reporting. DQRs may be conducted internally by MCA-Moçambique and MCC M&E staff, or by a third-party. DQRs should review data against the following standards: accuracy, consistency, timeliness and transparency. The frequency and timing of DQRs must be set forth in the M&E Plan; however, in addition to a pre-implementation DQR, at least one DQR is required during implementation, and MCC may request a DQR at any time. DQRs should be timed to occur once the ITT reflects several quarters of reporting but early enough in the Compact Term that meaningful remedial measures (if any) may be taken depending on the results of the review.
Data Quality Reviews. As determined in the M&E Plan or as otherwise requested by MCC, the quality of the data gathered through the M&E Plan will be reviewed to ensure that data reported are as reliable, timely and valid as resources will allow. The objective of any data quality review will be to verify the quality and the consistency of performance data, across different implementation units and reporting institutions. Such data quality reviews also will serve to identify where consistent levels of quality are not possible, given in-country capacity or other constraints. MCA-Lesotho will enter into an agreement (in a form acceptable to MCC) with the Reviewer to fulfill the provisions set forth in Section 1 of this Annex III and this clause (c).
Data Quality Reviews. Ensuring that all data collected from surveys, GRN agencies or other sources is reliable, accurate, and consistent is critical in order to use the data for decision-making, drawing conclusions about programme outcomes and impacts, and conducting final evaluations of activities. In collaboration with the Namibia Statistics Agency (NSA), NPC may conduct regular data quality reviews on all data sources. While this effort would be for the broader national M&E framework, relevant post-Compact M&E data sources would benefit from such review. Data quality reviews address the following (among others): • The prerequisites of data quality (i.e., legal framework, resources, relevance, and quality management) • Assurances of integrity • Methodological soundness (e.g., concepts and definitions, approaches/study design, and sampling methodologies) • Validity, reliability, timeliness, and precision of all data (including data collection instruments and procedures, data entry and storage, and data analysis) • Serviceability (i.e., periodicity and dissemination standards, consistency, and revision policies and practices) The results of all data quality reviews will be thoroughly documented, including the methodology used to conduct them, all major findings and issues, and recommendations for addressing any concerns or problems identified. Further, NPC’s plans for follow-up, including which recommendations will be implemented, will be documented for all stakeholders’ information. Findings related to post-Compact M&E indicators will be shared directly with MCC. MCC may also conduct independent data quality reviews, as needed, which NPC will help facilitate to the extent feasible.
Data Quality Reviews. As determined in the M&E Plan or as otherwise requested by MCC, the quality of the data gathered through the M&E Plan shall be reviewed to ensure that data reported are as reliable, timely and valid as resources allow. The objective of any data 12 All figures refer to the population within the areas targeted by the project, 60% of the country. The M&E Plan will disaggregate figures by breast cancer, cervical cancer, hypertension, and diabetes for the respective indicators. The figures presented here are the average of the two diseases (breast with cervical cancer and hypertension with diabetes). 13 In 2006, there were 17 women treated for breast cancer and 113 treated for cervical cancer (113 treated). These are national figures; the M&E Plan may choose to track figures specific to the target regions. 14 The baseline for screening for breast and cervical cancer will be determined during Year 1 of the Compact.
Data Quality Reviews. Data Quality Reviews (“DQR”) are a mechanism to review and analyze the utility, objectivity and integrity of performance information. DQRs are to cover: a) quality of data, b) data collection instruments, c) survey sampling methodology, d) data collection procedures, e) data entry, storage and retrieval processes, f) data manipulation and analyses and g) data dissemination. MCC requires that an independent entity conduct the DQR, such as a local or international specialized firm or research organization, or an individual consultant, depending on the size of the Program or Project in review. The frequency and timing of data quality reviews must be set forth in the M&E Plan; however MCC may request a DQR at any time. DQRs should be timed to occur before or early enough in the Compact Term that meaningful remedial measures (if any) may be taken depending on the results of the review. The methodology for the review should include a mix of document and record reviews, site visits, key informant interviews, and focus groups. All MCC’s common indicators listed in the Compact’s ITT will be included in the DQR.
