We provide evidence on the extent to which survey items in the Preference Survey Module and the resulting Global Preference Survey measuring social preferences—trust, altruism, positive and negative reciprocity—predict behavior in corresponding experimental games outside the original participant sample of Falk et al. (Manag Sci, 2022. https://doi.org/10.1287/mnsc.2022.4455). Our results, which are based on a replication study with university students in Tehran, Iran, are mixed. While quantitative items considering hypothetical versions of the experimental games correlate significantly and economically meaningfully with individual behavior, none of the qualitative items show significant correlations. The only exception is altruism where results correspond more closely to the original findings.

Cognitive diagnosis models (CDMs) are an important psychometric framework for classifying students in terms of attribute and/or skill mastery. The $\mathit{Q}$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\varvec{Q}$$\end{document} matrix, which specifies the required attributes for each item, is central to implementing CDMs. The general unavailability of $\mathit{Q}$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\varvec{Q}$$\end{document} for most content areas and datasets poses a barrier to widespread applications of CDMs, and recent research accordingly developed fully exploratory methods to estimate Q. However, current methods do not always offer clear interpretations of the uncovered skills and existing exploratory methods do not use expert knowledge to estimate Q. We consider Bayesian estimation of $\mathit{Q}$\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$$\varvec{Q}$$\end{document} using a prior based upon expert knowledge using a fully Bayesian formulation for a general diagnostic model. The developed method can be used to validate which of the underlying attributes are predicted by experts and to identify residual attributes that remain unexplained by expert knowledge. We report Monte Carlo evidence about the accuracy of selecting active expert-predictors and present an application using Tatsuoka’s fraction-subtraction dataset.

The validity of a test is often estimated in a nonrandom sample of selected individuals. To accurately estimate the relation between the predictor and the criterion we correct this correlation for range restriction. Unfortunately, this corrected correlation cannot be transformed using Fisher's Z transformation, and asymptotic tests of hypotheses based on small or moderate samples are not accurate. We developed a Fisher r to Z transformation for the corrected correlation for each of two conditions: (a) the criterion data were missing due to selection on the predictor (the missing data were MAR); and (b) the criterion was missing at random, not due to selection (the missing data were MCAR). The two Z transformations were evaluated in a computer simulation. The transformations were accurate, and tests of hypotheses and confidence intervals based on the transformations were superior to those that were not based on the transformations.

This rejoinder responds to the commentary by Liu (Psychometrika, 2015) entitled “On the consistency of Q-matrix estimation: A commentary” on the paper “A general method of empirical Q-matrix validation” by de la Torre and Chiu (Psychometrika, 2015). It discusses and addresses three concerns raised in the commentary, namely the estimation accuracy when a provisional Q-matrix is used, the consistency of the Q-matrix estimator, and the computational efficiency of the proposed method.

In contrast to unidimensional item response models that postulate a single underlying proficiency, cognitive diagnosis models (CDMs) posit multiple, discrete skills or attributes, thus allowing CDMs to provide a finer-grained assessment of examinees’ test performance. A common component of CDMs for specifying the attributes required for each item is the Q-matrix. Although construction of Q-matrix is typically performed by domain experts, it nonetheless, to a large extent, remains a subjective process, and misspecifications in the Q-matrix, if left unchecked, can have important practical implications. To address this concern, this paper proposes a discrimination index that can be used with a wide class of CDM subsumed by the generalized deterministic input, noisy “and” gate model to empirically validate the Q-matrix specifications by identifying and replacing misspecified entries in the Q-matrix. The rationale for using the index as the basis for a proposed validation method is provided in the form of mathematical proofs to several relevant lemmas and a theorem. The feasibility of the proposed method was examined using simulated data generated under various conditions. The proposed method is illustrated using fraction subtraction data.

Wild species of rice possess tremendous genetic variations and harbour resistance genes for biotic stresses. Bacterial blight (BB), caused by Xanthomonas oryzae pv. oryzae (Xoo), is a major disease affecting rice production globally. The current study characterized 116 accessions from 17 species of Oryza for BB disease during three seasons viz., kharif 2020, rabi 2020–21, kharif 2021 using an isolate of Xanthomonas oryzae pv. oryzae (Xoo) strain IX-020. A total of 40 accessions including Oryza rufipogon, O. nivara, O. officinalis and O. australiensis showed consistence resistance to the bacterial blight disease across the seasons. These accessions were further subjected to molecular characterization using 11 Xa genes viz., Xa4, xa5, xa13, Xa21, Xa23, Xa27(t), Xa32(t), Xa33, Xa35(t), Xa38 and xa41 with gene-specific markers to ascertain the novelty. Some key resistance genes such as Xa4, Xa23, Xa27(t), Xa32(t), Xa33, Xa35(t) and xa41 were detected in multiple accessions, with O. rufipogon and O. eichingeri harbouring particularly complex combinations of these genes. Notably, several accessions viz., IC521672 (O. nivara), EC861665 (O. officinalis), EC861677 (O. latifolia), EC861711 (O. punctata) and EC861738 (O. eichingeri) did not show the presence of any known genes indicating the possibility of novel genetic loci conferring BB resistance in these wild species. These promising accessions identified in the study are potential novel sources for bacterial leaf blight resistance in rice and will be useful for the development of durable bacterial blight resistance rice cultivars.

No study has validated questionnaires for assessing easily calculable diet quality scores in Japan. The Brief-type self-administered Diet History Questionnaire (BDHQ) is widely used to assess dietary intake in Japan, while the Meal-based Diet History Questionnaire (MDHQ) assesses dietary intake for each meal (breakfast, lunch, dinner and snacks) and overall dietary intake. This study examined the relative validity of the BDHQ and MDHQ for assessing three diet quality scores in Japanese adults. A total of 111 women and 111 men aged 30–76 years completed the web MDHQ and BDHQ, followed by 4-non-consective-day weighed dietary records. The diet quality scores examined included the Diet Quality Score for Japanese (DQSJ), Dietary Approaches to Stop Hypertension (DASH) score and Alternate Mediterranean Diet (AMED) score. The means of the three scores for overall diet from the BDHQ were not significantly different from those from the dietary records in both sexes, whereas those from the MDHQ were higher than those from the dietary records, except for the DASH and AMED in women. Pearson’s correlation coefficients between both questionnaires and dietary records were 0·57–0·63 for DQSJ, 0·49–0·57 for DASH and 0·31–0·49 for AMED across both sexes and both questionnaires. For each meal, Pearson’s correlation coefficients between the MDHQ and dietary records ranged from 0·01 (DASH for snacks in women) to 0·55 (DQSJ for breakfast in men), with a median of 0·35. This study showed that the ability of the BDHQ and MDHQ to rank individuals was good for DQSJ and DASH and acceptable for AMED.

The Mediterranean Region registers an increasing prevalence of obesity. The region lacks a diet screener to assess obesogenic nutrients. This study aimed to evaluate the reproducibility and validity of the Modified Mediterranean Prime Screen (MMPS) in estimating obesogenic nutrients’ intake among women of reproductive age, as compared with a culturally validated Food Frequency Questionnaire (FFQ), in Lebanon. We developed the MMPS consisting of thirty-two food/beverage items specific to the Lebanese Mediterranean culture. The MMPS and FFQ were administered in two visits (2 weeks–6 months apart), face to face and via telephone during the coronavirus disease 2019 pandemic. The reproducibility and validity of the MMPS were assessed using intraclass correlation coefficients (ICC) and Pearson’s correlations, respectively. The study included 143 women, aged 31·5 (sd 4·6) years, BMI 24·2 (sd 4·0) kg/m2, 87 % with university education and 91 % food secure. The reproducibility of the MMPS was moderate for energy and all assessed nutrients except for SFA (ICC = 0·428). The agreement of the MMPS with the reference FFQ was adequate for energy and obesogenic nutrients. Yet, the Pearson correlations for energy-adjusted nutrient intake were low for trans-fatty acids (0·294) and PUFA (0·377). The MMPS can be a time-efficient tool for dietary assessment of energy and many obesogenic nutrients. Future studies should validate the MMPS across the lifespan and re-evaluate it after updating the fatty acid profiles in the culturally specific food composition tables.

Using foresight methods such as scenarios, possible futures can be described and anticipated. Needs and requirements as well as product properties can be derived from that, which is necessary to plan successful products for future customers. Changes that occur in the future development can be identified with monitoring and the expected future can be adjusted. A consistent understanding of the use of monitoring for the product engineering process does not exist and is developed in this paper. Thereby, monitoring is considered in the context of validation and located in iPeM.

The European Green Deal aims to reduce global emissions by minimizing the use of resources. Early validation of products helps to reduce rework, costs and therefore resources. However, validation of complex mechatronic products is challenging due to interdependencies. Companies are applying systems engineering to meet this challenge. Current validation approaches are insufficient in the early design phases. This paper presents an approach to validation using the system architecture in the B2B sector. A machine tool and a custom built machine are presented as evaluation examples.

The ability to provide adequate nutrition is considered a key factor in evaluating the sustainability of foods and diets. Nutrient indices are used as functional units (FU) in life cycle assessment of foods to include nutritional performance in the environmental assessment of a product. Several general and food-group-specific nutrient indices exist but many lack validation, particularly when used as FU. In addition, the nutrient selection strategies and reference units for nutrient intake can vary considerably among studies. To validate intake-based product-group-specific nutrient indices previously developed for protein (NR-FIprot) and carbohydrate (NR-FIcarb) foods and for fruits and vegetables (NR-FIveg), we applied principal component analysis to investigate correlations between nutrients in foods and dishes representing a typical Finnish diet. The reference amounts for meal components were based on a plate model that reflected Finnish dietary recommendations. The portion sizes for the different food groups were anchored at 100 g, 135 g and 350 g for proteins, carbohydrates and fruits/vegetables, respectively. Statistical modelling largely validated the NR-FI indices, highlighting protein foods as sources of niacin, vitamin B12 and Se, carbohydrate foods as sources of Mg, Fe and phosphorous, and fruits/vegetables as sources of potassium, vitamin K, vitamin C, fibre and thiamine. However, in contrast to the intake-based approach applied in NR-FIprot, the dietary recommendation-based validation process suggested that fruits and vegetables should be favoured as sources of riboflavin and vitamin B6.

Dietary carotenoids are associated with lower risk of CHD. Assessment of dietary carotenoid intake using questionnaires can be susceptible to measurement error. Consequently, there is a need to validate data collected from FFQs which measure carotenoid intake. This study aimed to assess the performance of the Cardio-Med Survey Tool (CMST)-FFQ-version 2 (v2) as a measure of dietary carotenoid intake over 12-months against plasma carotenoids biomarkers and 7-Day Food Records (7DFR) in an Australian cardiology cohort. Dietary carotenoid intakes (β- and α-carotene, lycopene, β-cryptoxanthin and lutein/zeaxanthin) were assessed using the 105-item CMST-FFQ-v2 and compared to intakes measured by 7DFR and plasma carotenoid concentrations. Correlation coefficients were calculated between each dietary method, and validity coefficients (VCs) were calculated between each dietary method and theoretical true intake using the ‘methods of triads’. Thirty-nine participants aged 37–77 years with CHD participated in the cross-sectional study. The correlation between FFQ and plasma carotenoids were largest and significant for β-carotene (0.39, p=0.01), total carotenoids (0.37, p=0.02) and β-cryptoxanthin (0.33, p=0.04), with weakest correlations observed for α-carotene (0.21, p=0.21) and lycopene (0.21, p=0.21). The FFQ VCs were moderate (0.3–0.6) or larger for all measured carotenoids. The strongest were observed for total carotenoids (0.61) and β-carotene (0.59), while the weakest were observed for α-carotene (0.33) and lycopene (0.37). In conclusion, the CMST-FFQ-v2 measured dietary carotenoids intakes with moderate confidence for most carotenoids, however, there was less confidence in ability to measure α-carotene and lycopene intake, thus further research is warranted using a larger sample.