Zarówno na świecie, jak i w kraju zauważalny jest wzrost zainteresowania crowdfundingiem. Coraz więcej platform i projektów odnosi sukcesy i coraz szerzej rozpowszechnia się ten model pozyskiwania kapitału. Celem niniejszego artykułu jest przedstawienie potencjalnego zaangażowania się polskich internautów w realizację projektów finansowanych za pośrednictwem dedykowanych platform internetowych. W artykule omówiono założenia przeprowadzonego badania oraz uzyskane wyniki. Badanie przeprowadzono wśród polskich internautów za pomocą ankiety. Kwestionariusz opracowano w formie cyfrowej, który został przygotowany z wykorzystaniem narzędzia Typeform. Artykuł kończy podsumowanie zawierające wnioski z przeprowadzonego badania.
Indirect methods of questioning are of utmost importance when dealing with sensitive questions. This paper refers to the new indirect method introduced by Tian et al. (2014) and examines the optimal allocation of the sample to control and treatment groups. If determining the optimal allocation is based on the variance formula for the method of moments (difference in means) estimator of the sensitive proportion, the solution is quite straightforward and was given in Tian et al. (2014). However, maximum likelihood (ML) estimation is known from much better properties, therefore determining the optimal allocation based on ML estimators has more practical importance. This problem is nontrivial because in the Poisson item count technique the study sensitive variable is a latent one and is not directly observable. Thus ML estimation is carried out by using the expectation-maximisation (EM) algorithm and therefore an explicit analytical formula for the variance of the ML estimator of the sensitive proportion is not obtained. To determine the optimal allocation of the sample based on ML estimation, comprehensive Monte Carlo simulations and the EM algorithm have been employed.
The paper introduces a new item count technique (ICT) for dealing with sensitive features. One of the aims of the proposed method is to eliminate both the “ceiling” and “floor” effects that can occur in the original ICT. In the new model, in contrast to the classical one and recently proposed models, the two groups into which the sample is split are treated similarly. Therefore, there is no traditional distinction between the control and treatment groups. The control variable can be either a qualitative count variable or a continuous variable. To our knowledge, ICT methods with continuous control have not been proposed before. Although our new model differs substantially in the approach, it requires only a slight modification of the questionnaire design, which in no way leaks respondents’ privacy. Substantial gain in statistical efficiency is achieved as compared to the earlier proposed Poisson and negative binomial ICTs. The new method also reduces the bias of maximum likelihood estimators and allows to obtain bootstrap confidence intervals with a substantially smaller width. The statistical properties of the method are investigated theoretically and by simulations.
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