To conduct a proper biostatistical analysis of Lp(a) carrier state and ASCVD score with patients who ended up with coronary artery disease, you will need to follow these steps:
Define the research question: Determine the specific research question that you want to answer. For example, the research question could be "Does Lp(a) carrier state and ASCVD score affect the risk of developing coronary artery disease?"
Choose the study design: Select an appropriate study design based on your research question. For example, a case-control study or a cohort study might be appropriate.
Define the study population: Determine the characteristics of the study population, such as age, gender, race, and other relevant demographics.
Determine the sample size: Calculate the sample size required for the study based on the expected effect size and statistical power.
Collect data: Collect data on Lp(a) carrier state, ASCVD score, and other relevant variables from the study population.
Analyze data: Analyze the collected data using appropriate statistical methods. For example, you could use logistic regression to determine the odds ratio for developing coronary artery disease based on Lp(a) carrier state and ASCVD score.
Interpret results: Interpret the results of the statistical analysis and draw conclusions based on the research question.
Communicate findings: Communicate the findings of the study to the scientific community through a research paper or presentation.
It is important to note that conducting a biostatistical analysis requires a solid understanding of statistical methods, and it may be beneficial to consult with a statistician or biostatistician for assistance with the study design and analysis.
Les statistiques peuvent contribuer et aussi apporter un plus aux données obtenues (analyses et.. ASCVD) dans plusieurs domaines de la santé en particulier. Les méthodes sont nombreuses, cependant on retient l'analyse de la variance, la méthode des moindres carrés (corrélations), l'analyse multidimensionnelle, etc...
Il me semble qu'il faut obtenir beaucoup de résultats (répétitions) à travers les différentes répétitions (de l'expérimentation) pour pouvoir s'engager et utiliser les statistiques. Il restera l'interprétation à mener!