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#SCAPE_Research101
Sensitivity analyses in meta-analyses involve conducting alternative analyses by making specific changes to the methodology or inclusion criteria to assess the robustness of the results.
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ROB2 (Risk of Bias 2) is a widely used tool for assessing the risk of bias in randomized controlled trials (RCTs) included in systematic reviews and meta-analyses.
It was developed by the Cochrane Collaboration and provides a more comprehensive and structured approach compared to the Cochrane Collaboration's Risk of Bias Tool.
- ROB2 evaluates five domains of bias:
1- Randomization Process
2- Deviations from Intended Interventions
3- Missing Outcome Data
4- Measurement of the Outcome
5- Selection of Reported Results.
Each domain is assessed as having a low, some concerns, or high risk of bias.
⭐️In addition to the bias assessment for each domain, ROB2 also provides guidance for assigning an overall risk of bias judgment for each outcome within a study.
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The Jadad scale is a widely used tool for assessing the methodological quality of clinical trials included in meta-analysis.
It is a simple and quick tool that can help researchers and clinicians evaluate the reliability and validity of study results.
The Jadad scale focuses on three key methodological criteria in clinical trials:
1. Randomization: Was the study described as randomized? (1 point for yes, 0 points for no)
2. Double-blinding: Was the study described as double-blind? (1 point for yes, 0 points for no)
3. Withdrawals and dropouts: Was there a description of withdrawals and dropouts? (1 point for yes, 0 points for no)
The total score on the Jadad scale ranges from 0 to 5, with higher scores indicating better methodological quality.
- A score of 3 or more is generally considered to indicate a high-quality study.
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Assessing the risk of bias in a meta-analysis of randomized controlled trials (RCTs) is crucial to ensure the reliability and validity of the findings.
Cochrane Risk of Bias Tool has developed a widely used tool for assessing the risk of bias in RCTs included in the meta-analysis.
It evaluates various domains, including:
Random sequence generation,
Allocation concealment,
Blinding of participants and personnel,
Blinding of outcome assessment,
Incomplete outcome data,
Selective reporting, and other biases.
Each domain is assessed as having a
🟢 Low risk of bias
🔴 High risk of bias
🟡 Unclear risk of bias
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The DeLong test is used to compare two models by assessing the change in AUC.
⬇️🎥 Watch for more
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A variance inflation factor (VIF) is a measure of the amount of multi- collinearity in linear regression analysis
For more see the below ⬇️
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Akaike's information criterion (AIC) and Bayesian information criterion (BIC) are used in Linear and logistic regression
The BIC is more useful in selecting a correct model while the AIC is more appropriate in finding the best model for predicting future observations.
👇For more check out the below below
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Post Regression Analysis Assessment
To continue on the several ways to conduct the linear and logistic regression
Hosmer-Lemeshow test is another statistical method can be utilized
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Post Regression Analysis Assessment
There are several ways to conduct the linear and logistic regression
One of which is Area under the curve (AUC)
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The statistical combination of results from two or more separate studies is called Meta-analysis study 📚
In a meta-analysis, the results are typically presented in the form of forest plots,
🔺👇 For more about meta-analysis
#SCAPE_Research101
To conduct high quality research and providing valid data by analysis, researchers must be aware of their data and which test to use accordingly
For more details see the infographic below 🔽
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The researchers utilize statistical techniques to construct an artificial control group by matching each treated unit with a non-treated unit of similar characteristics by using Propensity score matching (PSM)
For more information about PSM👇
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There are several approaches for analysis of a survival outcome, one of which is Cox proportion hazards regression.
For more information watch the video below 👇
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📊Regression analysis is a statistical technique used to investigate the relationship between a dependent variable and one or more independent variables.
There are several types of regression analysis, each suitable for different types of data and research questions📈.
📄Here are some common types of regression analysis
#SCAPE_Research101
When conducting a research, several points should be consied in order to choose the appropriate statistical Tests, one of which the type of data.📊
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Various statistical analysis methods can be employed to identify differences between groups or conditions. However, these methods may not be essential when dealing with a large (huge) effect size, as we are not usually evaluating a "magic bullet." Typically, the focus is on evaluating small effect sizes, often in the range of 10-30% or even smaller, which are statistically difficult to assess but clinically meaningful. Therefore, by applying appropriate statistical techniques, researchers can assess the validity and practical importance of these small effect sizes, adding depth and insight to their findings and the clinical relevance of the observed differences.
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Null hypothesis(H0) vs Alternative hypothesis (Ha)
The entire research turns around the null hypothesis(H0) and alternative hypothesis (Ha).
A research hypothesis is the development of the research question (s), including a supportive hypothesis and objectives created by researchers.
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𝐈𝐧𝐭𝐞𝐫𝐧𝐚𝐥 𝐯𝐚𝐥𝐢𝐝𝐢𝐭𝐲 𝐚𝐧𝐝 𝐞𝐱𝐭𝐞𝐫𝐧𝐚𝐥 𝐯𝐚𝐥𝐢𝐝𝐢𝐭𝐲 are two important concepts in research design that related to the reliability and generalizability of study findings .. 📖✨
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#SCAPE_Research101 Prevalence refers to proportion of persons who have a condition at or during a particular time period, whereas incidence refers to the proportion or rate of persons who develop a condition during a particular time period.
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