Update to a program for saving a model fit as a dataset



Stata Technical Bulletin

43


Th The proportion of study subjects one expects the first observer to rate as positives (or the 1st observation in the case or a
test-retest reproducibility study). sskdlg uses the default value of 0.1 when the dialog box is opened.

ρ2 The proportion of study subjects one expects the second observer to rate as positives (or observation). sskdlg uses the
same default value as for
p1.

T The envisaged absolute precision, i.e., the difference between kappa and its lower (or upper) 1 — a confidence limit.
Acceptable values range from > 0 to a limit where, given a set of marginal values (pɪ and p2), values of
d entailing
b — b below the minimum possible value of kappa (κmin) or к + a above the maximum possible value of kappa (κmaχ) are
disallowed. If both conditions are satisfied, sskdlg returns a message warning that the sample size will not be calculated.
If only one of those occurs, the user is warned that there is a partial incompatibility between the stated values of
d and κ.
Yet, the sample size is calculated since d is compatible with at least one of «’s boundary values.

CI Confidence level percent for the confidence interval. The default is 95%.

Several display and graphical options are available. Checking “Show value of Q” and “Show value of maximum Q” adds
those values to the sample size displayed in the Results window. The first check is simply the quantity that underlies the sample
size calculation. The second check requests the calculation of the largest possible value of
Q and the corresponding sample size.
his is important when the researcher is not prepared to make any prior assumption concerning kappa. The output also indicates
the maximum possible value of kappa, given the preset marginals
p1 and p2

Checking “Sample size for diff.” and filling in the desired value requests a unique value of the absolute precision (d), given
the other selected inputs. This enables the user to work backwards by finding out the precision corresponding to a preset sample
size.

There are 4 types of graphics that can be selected. Clicking the “Graph Q” button requests a graphical display of the Q
values according to a range of kappa values. The default range is 0 to 1.0 when the dialog box is opened. The editing boxes
(e.g., indicated by “X:kappa”) can be used to specify a desired range of values for the X-axis. This operates as a zooming
device. Changing values enables zooming in or out. Note that negative values are allowed although this should be unusual in
the context of reliability studies. The position of maximum possible value of kappa (κma
χ) can also be visualized in the graph
by checking “k_max”. Also note that when the specified parameters preclude the calculation of sample size, Graph Q will not
be (re)displayed. Values need to be reset in order to enable the graph.

Clicking the “Graph S” button requests a graphical display analogous to Graph Q but plots sample size instead. The same
editing boxes as for Graph Q to control the ж-axis (zooming) are used. “k_max” may also be checked. The same restrictions as
in Graph Q apply here too.

Clicking the “Graph P” button requests a graphical display of sample sizes according to the proportion of positives measured
by raters 1 and 2 when both are expected to find the same value and given the specified values of
κ, d and CI. The ж-axis
default range is 0 to 1.0. Nevertheless, Graph P will only show a range compatible with plausible sample sizes, since some
combinations of specified parameters are impossible. For zooming in or out, edit boxes indicated by “X:prop.” can be used.

Clicking the “Graph D” button requests a graphical display of the absolute precision for a range of prespecified sample
sizes. This display is an extension of “Sample size for diff.”. Sample size range (zooming) can be controlled using the edit boxes
indicated by “X:ssize”.

Finally, on leaving the dialog box, checking “Keep variables on exit” retains in memory essential variables used for
displaying Graphs Q, S, P and D. This enables the user to redraw new graphs at his/her own discretion. Note that values kept in
memory are those specified (on display) at the time of exit. This option requires at least running the program once or running a
viable configuration of parameters after an improper one precluded a calculation. This is because the underlying data is cleared
in this situation in order to avoid a mismatch between the parameters on screen (dialog box) and the data in memory generated
by a former viable run.

(Continued on next page)



More intriguing information

1. Hemmnisse für die Vernetzungen von Wissenschaft und Wirtschaft abbauen
2. Revisiting The Bell Curve Debate Regarding the Effects of Cognitive Ability on Wages
3. New Evidence on the Puzzles. Results from Agnostic Identification on Monetary Policy and Exchange Rates.
4. Globalization and the benefits of trade
5. How much do Educational Outcomes Matter in OECD Countries?
6. A Multimodal Framework for Computer Mediated Learning: The Reshaping of Curriculum Knowledge and Learning
7. AGRIBUSINESS EXECUTIVE EDUCATION AND KNOWLEDGE EXCHANGE: NEW MECHANISMS OF KNOWLEDGE MANAGEMENT INVOLVING THE UNIVERSITY, PRIVATE FIRM STAKEHOLDERS AND PUBLIC SECTOR
8. Accurate, fast and stable denoising source separation algorithms
9. The Triangular Relationship between the Commission, NRAs and National Courts Revisited
10. Prizes and Patents: Using Market Signals to Provide Incentives for Innovations
11. Dual Track Reforms: With and Without Losers
12. The name is absent
13. The name is absent
14. The name is absent
15. Olive Tree Farming in Jaen: Situation With the New Cap and Comparison With the Province Income Per Capita.
16. The name is absent
17. The WTO and the Cartagena Protocol: International Policy Coordination or Conflict?
18. Evidence-Based Professional Development of Science Teachers in Two Countries
19. Fiscal Sustainability Across Government Tiers
20. CAPACITAÇÃO GERENCIAL DE AGRICULTORES FAMILIARES: UMA PROPOSTA METODOLÓGICA DE EXTENSÃO RURAL