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Briefly describe the types of meta-analysis of genetic association research
There are six kinds of meta-analysis: routine meta-analysis, single-rate meta-analysis, meta-regression analysis, cumulative meta-analysis, network meta-analysis and diagnostic meta-analysis.

Meta-analysis is a secondary study, which is a re-study, synthesis and innovation of a series of original research results.

1, Definition: Data errors refer to the unconscious errors and omissions of researchers in the process of data collection, processing, analysis or reporting. These errors may be caused by technical problems, experimental equipment failure, improper experimental operation or statistical analysis errors.

Data fabrication refers to the behavior that researchers deliberately forge, fabricate or tamper with data in order to achieve the expected research results. This behavior violates the scientific research norms and the principle of good faith.

2. Objective: Data errors are usually unintentional and may be caused by negligence of researchers, technical problems or improper experimental operation. Data errors are usually unintentional, and researchers may not realize that there is something wrong with the data.

Data fraud is intentional, the purpose is to deceive others or obtain favorable research results, so as to enhance their reputation, obtain funds or achieve a certain purpose. Data fraud is a misconduct in scientific research, which violates the ethical principles of scientific research.

3. Methods: Data errors are usually unintentional and may be caused by improper experimental operation, technical problems or statistical analysis errors. Data errors may be accidental, random or systematic, but they are not intentional.

The tampering of data is intentional, and researchers may tamper with or tamper with the data to achieve their expected research results. Data fraud may include modifying data, deleting abnormal values and fabricating data.

4. Consequences: Although data errors may affect the accuracy and reliability of research, they are usually not regarded as scientific misconduct. When researchers realize the mistakes, they should correct them in time and provide correct data as much as possible.

Data fraud is a serious misconduct in scientific research. Once researchers are found to have falsified data, they will face the consequences of reputation damage, academic punishment and revocation of research results. Data fraud not only damages personal reputation, but also damages the overall credibility and ethical value of scientific research.

Matters needing attention in writing papers

1, clear organizational structure: the paper should have a clear organizational structure, including introduction, literature review, research methods, result analysis and discussion, conclusion and other parts. Each part should have clear content and be organized in logical order.