| 1. |
- Angelov, Angel G., et al.
(författare)
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Four-decision tests for stochastic dominance, with an application to environmental psychophysics
- 2019
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Ingår i: Journal of mathematical psychology (Print). - : Elsevier. - 0022-2496 .- 1096-0880. ; 93
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Tidskriftsartikel (refereegranskat)abstract
- If the survival function of a random variable X lies to the right of the survival function of a random variable Y, then X is said to stochastically dominate Y. Inferring stochastic dominance is particularly complicated because comparing survival functions raises four possible hypotheses: identical survival functions, dominance of X over Y, dominance of Y over X, or crossing survival functions. In this paper, we suggest four-decision tests for stochastic dominance suitable for paired samples. The tests are permutation-based and do not rely on distributional assumptions. One-sided Cramér–von Mises and Kolmogorov–Smirnov statistics are employed but the general idea may be utilized with other test statistics. The power to detect dominance and the different types of wrong decisions are investigated in an extensive simulation study. The proposed tests are applied to data from an experiment concerning the individual’s willingness to pay for a given environmental improvement.
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| 2. |
- Angelov, Angel G., et al.
(författare)
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Maximum likelihood estimation for survey data with informative interval censoring
- 2019
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Ingår i: AStA Advances in Statistical Analysis. - : Springer. - 1863-8171 .- 1863-818X. ; 103:2, s. 217-236
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Tidskriftsartikel (refereegranskat)abstract
- Interval-censored data may arise in questionnaire surveys when, instead of being asked to provide an exact value, respondents are free to answer with any interval without having pre-specified ranges. In this context, the assumption of noninformative censoring is violated, and thus, the standard methods for interval-censored data are not appropriate. This paper explores two schemes for data collection and deals with the problem of estimation of the underlying distribution function, assuming that it belongs to a parametric family. The consistency and asymptotic normality of a proposed maximum likelihood estimator are proven. A bootstrap procedure that can be used for constructing confidence intervals is considered, and its asymptotic validity is shown. A simulation study investigates the performance of the suggested methods.
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| 3. |
- Angelov, Angel G., 1983-
(författare)
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Methods for interval-censored data and testing for stochastic dominance
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis includes four papers: the first three of them are concerned with methods for interval-censored data, while the forth paper is devoted to testing for stochastic dominance.In many studies, the variable of interest is observed to lie within an interval instead of being observed exactly, i.e., each observation is an interval and not a single value. This type of data is known as interval-censored. It may arise in questionnaire-based studies when the respondent gives an answer in the form of an interval without having pre-specified ranges. Such data are called self-selected interval data. In this context, the assumption of noninformative censoring is not fulfilled, and therefore the existing methods for interval-censored data are not necessarily applicable.A problem of interest is to estimate the underlying distribution function. There are two main approaches to this problem: (i) parametric estimation, which assumes a particular functional form of the distribution, and (ii) nonparametric estimation, which does not rely on any distributional assumptions. In Paper A, a nonparametric maximum likelihood estimator for self-selected interval data is proposed and its consistency is shown. Paper B suggests a parametric maximum likelihood estimator. The consistency and asymptotic normality of the estimator are proven.Another interesting problem is to infer whether two samples arise from identical distributions. In Paper C, nonparametric two-sample tests suitable for self-selected interval data are suggested and their properties are investigated through simulations.Paper D concerns testing for stochastic dominance with uncensored data. The paper explores a testing problem which involves four hypotheses, that is, based on observations of two random variables X and Y, one wants to discriminate between four possibilities: identical survival functions, stochastic dominance of X over Y, stochastic dominance of Y over X, or crossing survival functions. Permutation-based tests suitable for two independent samples and for paired samples are proposed. The tests are applied to data from an experiment concerning the individual's willingness to pay for a given environmental improvement.
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| 4. |
- Angelov, Angel G., et al.
(författare)
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Nonparametric estimation for self-selected interval data collected through a two-stage approach
- 2017
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Ingår i: Metrika (Heidelberg). - : Springer. - 0026-1335 .- 1435-926X. ; 80:4, s. 377-399
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Tidskriftsartikel (refereegranskat)abstract
- Self-selected interval data arise in questionnaire surveys when respondents are free to answer with any interval without having pre-specified ranges. This type of data is a special case of interval-censored data in which the assumption of noninformative censoring is violated, and thus the standard methods for interval-censored data (e.g. Turnbull's estimator) are not appropriate because they can produce biased results. Based on a certain sampling scheme, this paper suggests a nonparametric maximum likelihood estimator of the underlying distribution function. The consistency of the estimator is proven under general assumptions, and an iterative procedure for finding the estimate is proposed. The performance of the method is investigated in a simulation study.
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| 5. |
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| 6. |
- Angelov, Angel G., et al.
(författare)
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Quantile regression with interval-censored data in questionnaire-based studies
- 2024
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Ingår i: Computational statistics (Zeitschrift). - : Springer Berlin/Heidelberg. - 0943-4062 .- 1613-9658. ; 39:2, s. 583-603
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Tidskriftsartikel (refereegranskat)abstract
- Interval-censored data can arise in questionnaire-based studies when the respondent gives an answer in the form of an interval without having pre-specified ranges. Such data are called self-selected interval data. In this case, the assumption of independent censoring is not fulfilled, and therefore the ordinary methods for interval-censored data are not suitable. This paper explores a quantile regression model for self-selected interval data and suggests an estimator based on estimating equations. The consistency of the estimator is shown. Bootstrap procedures for constructing confidence intervals are considered. A simulation study indicates satisfactory performance of the proposed methods. An application to data concerning price estimates is presented.
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| 7. |
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| 8. |
- Angelov, Angel G., et al.
(författare)
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Tests of stochastic dominance with repeated measurements data
- 2023
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Ingår i: AStA Advances in Statistical Analysis. - : Springer. - 1863-8171 .- 1863-818X. ; 107:3, s. 443-467
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Tidskriftsartikel (refereegranskat)abstract
- The paper explores a testing problem which involves four hypotheses, that is, based on observations of two random variables X and Y, we wish to discriminate between four possibilities: identical survival functions, stochastic dominance of X over Y, stochastic dominance of Y over X, or crossing survival functions. Four-decision testing procedures for repeated measurements data are proposed. The tests are based on a permutation approach and do not rely on distributional assumptions. One-sided versions of the Cramér–von Mises, Anderson–Darling, and Kolmogorov–Smirnov statistics are utilized. The consistency of the tests is proven. A simulation study shows good power properties and control of false-detection errors. The suggested tests are applied to data from a psychophysical experiment.
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