OpenMx: mxComputeConfidenceInterval – R documentation

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mxComputeConfidenceInterval

Find likelihood-based confidence intervals

Description

There are various equivalent ways to pose the optimization problems required to estimate confidence intervals. Most accurate solutions are achieved when the problem is posed using non-linear constraints. However, the available optimizers (CSOLNP, SLSQP, and NPSOL) often have difficulty with non-linear constraints.

Usage

mxComputeConfidenceInterval(
  plan,
  ...,
  freeSet = NA_character_,
  verbose = 0L,
  engine = NULL,
  fitfunction = "fitfunction",
  tolerance = NA_real_,
  constraintType = "none"
)

Arguments

`plan`	compute plan to optimize the model
`...`	Not used. Forces remaining arguments to be specified by name.
`freeSet`	names of matrices containing free variables
`verbose`	integer. Level of run-time diagnostic output. Set to zero to disable
`engine`	deprecated
`fitfunction`	the name of the deviance function
`tolerance`	deprecated
`constraintType`	one of c('ineq', 'none')

References

Neale, M. C. & Miller M. B. (1997). The use of likelihood based confidence intervals in genetic models. Behavior Genetics, 27(2), 113-120.

Pek, J. & Wu, H. (2015). Profile likelihood-based confidence intervals and regions for structural equation models. Psychometrika, 80(4), 1123-1145.

Wu, H. & Neale, M. C. (2012). Adjusted confidence intervals for a bounded parameter. Behavior genetics, 42(6), 886-898.

OpenMx

Extended Structural Equation Modelling

v2.19.5

Apache License (== 2.0)

Authors

Steven M. Boker [aut], Michael C. Neale [aut], Hermine H. Maes [aut], Michael J. Wilde [ctb], Michael Spiegel [aut], Timothy R. Brick [aut], Ryne Estabrook [aut], Timothy C. Bates [aut], Paras Mehta [ctb], Timo von Oertzen [ctb], Ross J. Gore [aut], Michael D. Hunter [aut], Daniel C. Hackett [ctb], Julian Karch [ctb], Andreas M. Brandmaier [ctb], Joshua N. Pritikin [aut, cre], Mahsa Zahery [aut], Robert M. Kirkpatrick [aut], Yang Wang [ctb], Ben Goodrich [ctb], Charles Driver [ctb], Massachusetts Institute of Technology [cph], S. G. Johnson [cph], Association for Computing Machinery [cph], Dieter Kraft [cph], Stefan Wilhelm [cph], Sarah Medland [cph], Carl F. Falk [cph], Matt Keller [cph], Manjunath B G [cph], The Regents of the University of California [cph], Lester Ingber [cph], Wong Shao Voon [cph], Juan Palacios [cph], Jiang Yang [cph], Gael Guennebaud [cph], Jitse Niesen [cph]

Initial release

2021-03-26