Empirical cycle checklist
Observation:
- what is the background of the research the authors performed?
- what was the problem the authors aimed to investigate?
- what is existing knowledge regarding this problem?
Induction:
- did the authors state a hypothesis and if yes, what is the hypothesis?
- in case there is no hypothesis, what is the research question?
Deduction:
- what experimental approach did the authors use to test the
hypothesis/answer the research question?
- in case multiple experiments were performed, describe for each experiment
the rationale to perform it and the question to be answered
Testing:
- describe how the authors collected data by making use of the experimental
set-up.
- what do the data in every figure/table represent?
- what kind of statistics was used?
Evaluation:
- how did the authors interpret their data?
- how did the authors explain their data?
- what conclusions did the authors drew based on their data?
Additional question:
What type of study is represented by this article (e.g. observational study, randomized
control trial, experimental, etc.)? Argue your choice!
CABP report
1. Describe the research question(s)/hypotheses/objective(s) of the study in your own words.
2. What was the rationale for performing this study?
3. For each research question/hypothesis/objective describe:
3a. the research design that was used;
3b. the participants/samples that were used;
3c. the statistical analysis that was used;
3d. the main findings;
3e. the conclusion.
4. Explain why the conclusion is/isn’t in line with the findings?
5. What was done to avoid/minimise bias and/or confounding? What could the authors do to improve this even
further?
6. Describe the reference standard, index test, determinants and/or outcome measures that were used and
critically appraise whether the quality of the measurements was adequate. Why (not)?
7. Describe the limitations of this study in your own words. Were there any ambiguities you had about the study
that the authors didn’t mention?
8. Describe the strengths of this study in your own words.
9. Can the results be applied in wider range (e.g. the scenario population), (i.e. appraise the external validity of the
study)?
10. Bottom line: what is the quality of the study?
Observation – Question – Hypothesis – Prediction – Test – Conclusion
, (pre-) stratification- The partitioning of subjects and results by a factor other than the
treatment given (for example by gender or age). Stratification can be used to control for
confounding variables.
95% confidence interval- A type of interval estimate that might contain the true value
of an unknown population parameter.
95% confidence- Statisticians use a confidence interval to express the degree of
uncertainty associated with a sample statistic. A confidence interval is an interval
estimate combined with a probability statement. With a large sample size which
could represent a population. So, with a 95% confidence we would expect the
results to fall within the interval 95% of the time Intervals
Absolute Risk- The percentage tells you how much risk of an undesirable
outcome. Something happening is the odds of that happening over a stated period
of time.
Accuracy- accuracy describes the difference between the measurement and the
part's actual value, while precision describes the variation you see when you
measure the same part repeatedly with the same device. Deviation of a
measurement from the true value.
Ancillary analyses- A statistic whose sampling distribution does not depend
on the parameters of the model.
Associated- Having a connection/correlation with.
Attrition Bias- An error occurring due to participants selectively dropping out/ lost
to follow up.
Baseline date- Initial collection of data which serves as a basis for
comparison with the subsequently acquired data.
Observation:
- what is the background of the research the authors performed?
- what was the problem the authors aimed to investigate?
- what is existing knowledge regarding this problem?
Induction:
- did the authors state a hypothesis and if yes, what is the hypothesis?
- in case there is no hypothesis, what is the research question?
Deduction:
- what experimental approach did the authors use to test the
hypothesis/answer the research question?
- in case multiple experiments were performed, describe for each experiment
the rationale to perform it and the question to be answered
Testing:
- describe how the authors collected data by making use of the experimental
set-up.
- what do the data in every figure/table represent?
- what kind of statistics was used?
Evaluation:
- how did the authors interpret their data?
- how did the authors explain their data?
- what conclusions did the authors drew based on their data?
Additional question:
What type of study is represented by this article (e.g. observational study, randomized
control trial, experimental, etc.)? Argue your choice!
CABP report
1. Describe the research question(s)/hypotheses/objective(s) of the study in your own words.
2. What was the rationale for performing this study?
3. For each research question/hypothesis/objective describe:
3a. the research design that was used;
3b. the participants/samples that were used;
3c. the statistical analysis that was used;
3d. the main findings;
3e. the conclusion.
4. Explain why the conclusion is/isn’t in line with the findings?
5. What was done to avoid/minimise bias and/or confounding? What could the authors do to improve this even
further?
6. Describe the reference standard, index test, determinants and/or outcome measures that were used and
critically appraise whether the quality of the measurements was adequate. Why (not)?
7. Describe the limitations of this study in your own words. Were there any ambiguities you had about the study
that the authors didn’t mention?
8. Describe the strengths of this study in your own words.
9. Can the results be applied in wider range (e.g. the scenario population), (i.e. appraise the external validity of the
study)?
10. Bottom line: what is the quality of the study?
Observation – Question – Hypothesis – Prediction – Test – Conclusion
, (pre-) stratification- The partitioning of subjects and results by a factor other than the
treatment given (for example by gender or age). Stratification can be used to control for
confounding variables.
95% confidence interval- A type of interval estimate that might contain the true value
of an unknown population parameter.
95% confidence- Statisticians use a confidence interval to express the degree of
uncertainty associated with a sample statistic. A confidence interval is an interval
estimate combined with a probability statement. With a large sample size which
could represent a population. So, with a 95% confidence we would expect the
results to fall within the interval 95% of the time Intervals
Absolute Risk- The percentage tells you how much risk of an undesirable
outcome. Something happening is the odds of that happening over a stated period
of time.
Accuracy- accuracy describes the difference between the measurement and the
part's actual value, while precision describes the variation you see when you
measure the same part repeatedly with the same device. Deviation of a
measurement from the true value.
Ancillary analyses- A statistic whose sampling distribution does not depend
on the parameters of the model.
Associated- Having a connection/correlation with.
Attrition Bias- An error occurring due to participants selectively dropping out/ lost
to follow up.
Baseline date- Initial collection of data which serves as a basis for
comparison with the subsequently acquired data.
