This article explored the application of the posterior predictive model checking (PPMC) method in assessing fit for unidimensional polytomous item response theory (IRT) models, specifically the divide-by-total models (e.g., the generalized partial credit model). Previous research has primarily focused on using PPMC in model checking for unidimensional and multidimensional IRT models for dichotomous data, and has paid little attention to polytomous models. A Monte Carlo simulation was conducted to investigate the performance of PPMC in detecting different sources of misfit for the partial credit model family. Results showed that the PPMC method, in combination with appropriate discrepancy measures, had adequate power in detecting different sources of misfit for the partial credit model family. Global odds ratio and item total correlation exhibited specific patterns in detecting the absence of the slope parameter, whereas Yen's Q1 was found to be promising in the detection of misfit caused by the constant category intersection parameter constraint across items. (PsycINFO Database Record

Digital radio over fibre (RoF) technology has been suggested as a promising solution to replace conventional analogue RoF technology for multi-service in-building wireless coverage. However in conventional digital RoF, digitisation leads to high data rates which in turn results in high capital expenditure (CAPEX) and operational expenditure (OPEX). This paper investigates a novel methodology to transmit efficiently a digitised radio service over an optical link to provide wireless coverage. We demonstrate a digital processing technique that is able to compress the digitised 20MHz bandwidth Long Term Evolution (LTE) data stream to a much lower level than in a conventional link without impairing its radio performance.

Digital radio-over-fibre transmission has been studied extensively as a way of providing seamless last-mile wireless connectivity by carrying digitised radio frequency (RF) services over broadband optical infrastructures. With the growing demand on wireless capacity and the number of wireless services, a key challenge is the enormous scale of the digital data generated after the digitisation process. In turn, this leads to optical links needing to have very large capacity and hence, high capital expenditure (CAPEX). In this paper, we firstly present and then experimentally demonstrate a multiservice DRoF system for a neutral-host fronthaul link where both forward and reverse links use data compression, multiband multiplexing and synchronisation algorithms. The effect of a novel digital automatic gain control (DAGC) is comprehensively analysed to show an improved RF dynamic range alongside bit rate reduction. In this case, the system allows all cellular services from the three Chinese mobile network operators (MNOs) to be converged onto a single fiber infrastructure. We successfully demonstrate 14 wireless channels over a 10Gbps 20km optical link for indoor and outdoor wireless coverage, showing a minimum error value magnitude (EVM) of <8% and >60dB RF dynamic range. It is believed that the technology provides an ideal solution for last-mile wireless coverage in 5G and beyond. INDEX TERMS Digital radio over fiber, neutral host, cloud radio access network (C-RAN), multiband multiplexing, automatic gain control, 4G, 5G, fronthaul.

Compressed DRoF-based fronthaul links enable cost-effective last-mile wireless coverage. This paper demonstrates a novel system which carries 12 LTE services over both optical fibre and photonically-generated THz wireless links with over 40 dB dynamic range.

This paper demonstrates a novel digital radio over fibre (DRoF) architecture that is able to transport multiple compressed digitised RF services using both optical fibre and wireless millimetre wave (mmW) links. This solution has advantages as a cost effective indoor wireless infrastructure where flexible transmission schemes are required. Experimental results indicate wide RF dynamic range for two LTE services transmitted simultaneously, showing its capability for creating a neutral-host radio access network (RAN) with good spectral efficiency and cost effectiveness.

The C-test is a type of gap-filling test designed to efficiently measure second language proficiency. The typical C-test consists of several short paragraphs with the second half of every second word deleted. The words with deleted parts are considered as items nested within the corresponding paragraph. Given this testlet structure, it is commonly taken for granted that the C-test design may violate the local independence assumption. However, this assumption has not been fully investigated in the C-test research to date, including the evaluation of alternative psychometric models (i.e., unidimensional and multidimensional) to calibrate and score the C-test. This study addressed each of these issues using a large data set of responses to an English-language C-test. First, we examined the local item independence assumption via multidimensional item response theory (IRT) models, Yen’s Q3, and Jackknife Slope Index. Second, we evaluated several IRT models to determine optimal approaches to scoring the C-test. The results support an interpretation of unidimensionality for the C-test items within a paragraph, with only minor evidence of local item dependence. Furthermore, the two-parameter logistic (2PL) IRT model was found to be the most appropriate model for calibrating and scoring the C-test. Implications for designing, scoring, and analyzing C-tests are discussed.

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