Jonathan Gorard
Biographic Data
| ID | 6694352 |
|---|---|
| NAME | Jonathan Gorard |
| GIVEN NAMES | Jonathan |
| FAMILY NAME | Gorard |
| SIGNATURE | GORARD J |
| AFFILIATIONS | King's College London, London, UK |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 8 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2016 |
| H-INDEX | 1 |
Explaining the number of counterfactual cases needed to disturb a finding
This brief paper is an extension of our original paper What to do instead of significance testing? Calculating the ‘number of counterfactual cases needed to disturb a finding’, following a response by Jouni Kuha and Patrick Stugis. It shows how their response assists in the development of our idea of the ‘number needed to disturb’ (NNTD) a finding, and allows us to explain that idea further. NNTD allows researchers to summarise the scale, ‘effect…
What to do instead of significance testing? Calculating the ‘number of counterfactual cases needed to disturb a finding’
This brief paper introduces a new approach to assessing the trustworthiness of research comparisons when expressed numerically. The ‘number needed to disturb’ a research finding would be the number of counterfactual values that can be added to the smallest arm of any comparison before the difference or ‘effect’ size disappears, minus the number of cases missing key values. This way of presenting the security of findings has several advantages ove…
What to do instead of significance testing? Calculating the ‘number of counterfactual cases needed to disturb a finding’
This brief paper introduces a new approach to assessing the trustworthiness of research comparisons when expressed numerically. The ‘number needed to disturb’ a research finding would be the number of counterfactual values that can be added to the smallest arm of any comparison before the difference or ‘effect’ size disappears, minus the number of cases missing key values. This way of presenting the security of findings has several advantages ove…
Explaining the number of counterfactual cases needed to disturb a finding
This brief paper is an extension of our original paper What to do instead of significance testing? Calculating the ‘number of counterfactual cases needed to disturb a finding’, following a response by Jouni Kuha and Patrick Stugis. It shows how their response assists in the development of our idea of the ‘number needed to disturb’ (NNTD) a finding, and allows us to explain that idea further. NNTD allows researchers to summarise the scale, ‘effect…
What to do instead of significance testing? Calculating the ‘number of counterfactual cases needed to disturb a finding’
This brief paper introduces a new approach to assessing the trustworthiness of research comparisons when expressed numerically. The ‘number needed to disturb’ a research finding would be the number of counterfactual values that can be added to the smallest arm of any comparison before the difference or ‘effect’ size disappears, minus the number of cases missing key values. This way of presenting the security of findings has several advantages ove…
Explaining the number of counterfactual cases needed to disturb a finding
This brief paper is an extension of our original paper What to do instead of significance testing? Calculating the ‘number of counterfactual cases needed to disturb a finding’, following a response by Jouni Kuha and Patrick Stugis. It shows how their response assists in the development of our idea of the ‘number needed to disturb’ (NNTD) a finding, and allows us to explain that idea further. NNTD allows researchers to summarise the scale, ‘effect…
Attrition (2 works) · Computer Science (2 works) · Counterfactual thinking (2 works) · Econometrics (2 works) · Psychology (2 works) · Social Psychology (2 works) · Social Psychology (2 works) · Economics (1 works) · Experimental Behavioral Economics Studies (1 works) · Extension (predicate logic (1 works)