Description Usage Arguments Value Author(s) References See Also Examples

`dstudy`

runs a D-study from the results of a `gstudy`

and computes, for a
certain number of queries, the expected generalizability coefficient `Erho2`

and index of
dependability `Phi`

, possibly with confidence intervals. Alternatively, it can estimate the
number of queries needed to achieve a certain level of stability, also with confidence intervals.

1 | ```
dstudy(gdata, queries = gdata$n.q, stability = 0.95, alpha = 0.025)
``` |

`gdata` |
The result of running a |

`queries` |
A vector with different query set sizes for which to estimate Erho2 and Phi.
Defaults to the number of queries used to compute |

`stability` |
A vector with target Erho2 and Phi values to estimate required query set sizes. |

`alpha` |
A vector of confidence levels to compute intervals for Erho2, Phi and query set
sizes. This is the probability on each side of the interval, so for a 90% confidence interval
one must set |

An object of class `dstudy`

, with the following components:

`Erho2` , `Erho2.lwr` , `Erho2.upr` | Expected generalizability coefficient, and lower and upper limits of the intervals around it. |

`Phi` , `Phi.lwr` , `Phi.upr` | Expected index of dependability, and lower and upper limits of the intervals around it. |

`n.q_Erho2` , `n.q_Erho2.lwr` , `n.q_Erho2.upr` | Expected number of queries to achieve the generalizability coefficient, and lower and upper limits of the intervals around it. |

`n.q_Phi` , `n.q_Phi.lwr` , `n.q_Phi.upr` | Expected number of queries to achieve the index of dependability, and lower and upper limits of the intervals around it. |

`call` | A list with the `gstudy` used in this D-study, the target number of
`queries` , target level of `stability` and `alpha` level for the confidence
intervals. |

Juli<c3><a1>n Urbano

R.L. Brennan (2001). Generalizability Theory. Springer.

L.S. Feldt (1965). The Approximate Sampling Distribution of Kuder-Richardson Reliability Coefficient Twenty. Psychometrika, 30(3):357<e2><80><93>370.

C. Arteaga, S. Jeyaratnam, and G. A. Franklin (1982). Confidence Intervals for Proportions of Total Variance in the Two-Way Cross Component of Variance Model. Communications in Statistics: Theory and Methods, 11(15):1643<e2><80><93>1658.

J. Urbano, M. Marrero and D. Mart<c3><ad>n (2013). On the Measurement of Test Collection Reliability. ACM SIGIR, pp. 393-402.

1 2 3 4 5 6 7 8 9 10 11 | ```
g <- gstudy(adhoc3)
dstudy(g)
# estimate stability at various query set sizes
dstudy(g, queries = seq(50, 200, 10))
# estimate required query set sizes for various stability levels
dstudy(g, stability = seq(0.8, 0.95, 0.01))
# compute both 95% and 99% confidence intervals
dstudy(g, stability = 0.9, alpha = c(0.05, 0.01) / 2)
# compute 1-tailed 95% confidence intervals
dstudy(g, alpha = 0.05)
``` |

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