The relevance of syntactic complexity for truth judgments: A registered report.

Fluency theories predict higher truth judgments for easily processed statements. We investigated two factors relevant for processing fluency: repetition and syntactic complexity. In three online experiments, we manipulated syntactic complexity by creating simple and complex versions of trivia statements. Experiments 1 and 2 replicated the repetition-based truth effect. However, syntactic complexity did not affect truth judgments although complex statements were processed slower than simple statements. This null effect is surprising given that both studies had high statistical power and varied in the relative salience of syntactic complexity. Experiment 3 provides a preregistered test of the discounting explanation by using improved trivia statements of equal length and by manipulating the salience of complexity in a randomized design. As predicted by fluency theories, simple statements were more likely judged as true than complex ones, while this effect was small and not moderated by the salience of complexity.

Measuring the variability of personality traits with interval responses: Psychometric properties of the dual-range slider response format : Measuring variability with interval responses.

Measuring the variability in persons' behaviors and experiences using ecological momentary assessment is time-consuming and costly. We investigate whether interval responses provided through a dual-range slider (DRS) response format can be used as a simple and efficient alternative: Respondents indicate variability in their behavior in a retrospective rating by choosing a lower and an upper bound on a continuous, bounded scale. We investigate the psychometric properties of this response format as a prerequisite for further validation. First, we assess the test-retest reliability of factor-score estimates for the width of DRS intervals. Second, we test whether factor-score estimates of the visual analog scale (VAS) and the location of DRS intervals show convergent validity. Third, we investigate whether factor-score estimates for the DRS are uncorrelated between different personality scales. We present a longitudinal multitrait-multimethod study using two personality scales (Extraversion, Conscientiousness) and two response formats (VAS, DRS) at two measurement occasions (6-8 weeks apart) for which we estimate factor-score correlations in a joint item response theory model. The test-retest reliability of the width of DRS intervals was high ( ρ ^ ≥ . 73 ). Also, convergent validity between location scores of VAS and DRS was high ( ρ ^ ≥ . 88 ). Conversely, discriminant validity of the width of DRS intervals between Extraversion and Conscientiousness was poor ( ρ ^ ≥ . 94 ). In conclusion, the DRS seems to be a reliable response format that could be used to measure the central tendency of a trait equivalently to the VAS. However, it might not be well suited for measuring intra-individual variability in personality traits.

A tutorial on Bayesian model-averaged meta-analysis in JASP.

Researchers conduct meta-analyses in order to synthesize information across different studies. Compared to standard meta-analytic methods, Bayesian model-averaged meta-analysis offers several practical advantages including the ability to quantify evidence in favor of the absence of an effect, the ability to monitor evidence as individual studies accumulate indefinitely, and the ability to draw inferences based on multiple models simultaneously. This tutorial introduces the concepts and logic underlying Bayesian model-averaged meta-analysis and illustrates its application using the open-source software JASP. As a running example, we perform a Bayesian meta-analysis on language development in children. We show how to conduct a Bayesian model-averaged meta-analysis and how to interpret the results.

Cheating to benefit others? On the relation between Honesty-Humility and prosocial lies.

OBJECTIVE: Among basic personality traits, Honesty-Humility yields the most consistent, negative link with dishonest behavior. The theoretical conceptualization of Honesty-Humility, however, suggests a potential boundary condition of this relation, namely, when lying is prosocial. We therefore tested the hypothesis that the association between Honesty-Humility and dishonesty weakens once lying benefits someone else, particularly so if this other is needy. METHODS: In two online studies (Study 1: N = 775 in Germany; Study 2: N = 737 in the UK, preregistered), we measured self-reported Honesty-Humility and dishonest behavior in incentivized cheating paradigms in which the beneficiary of participants' dishonesty was either the participants themselves, a "non-needy" other (e.g., another participant), or a "needy" other (e.g., a charity). RESULTS: We found support for the robustness of the negative association between Honesty-Humility and dishonesty, even if lying was prosocial. CONCLUSION: Individuals high in Honesty-Humility largely prioritize honesty, even if there is a strong moral imperative to lie; those low in Honesty-Humility, by contrast, tend to lie habitually and thus even if they themselves do not directly profit monetarily. This suggests that (un)truthfulness may be an absolute rather than a relative aspect of Honesty-Humility, although further systematic tests of this proposition are needed.

Enabling Population Biology Studies of Stemphylium vesicarium from Onion with Microsatellites.

Stemphylium leaf blight (SLB), caused by the fungus Stemphylium vesicarium, is dominant within the foliar disease complex affecting onion production in New York (NY). The disease causes premature defoliation and significant reductions in bulb weight and quality. Foliar diseases of onion are usually managed by an intensive fungicide program, but SLB management is complicated by resistance to multiple single-site modes of action. The design of integrated disease management strategies is limited by incomplete knowledge surrounding the dominant sources of S. vesicarium inoculum. To facilitate genomic-based studies of S. vesicarium populations, nine microsatellite markers were developed. The markers were multiplexed into two PCR assays containing four and five fluorescently labeled microsatellite markers. Initial testing of the S. vesicarium isolates found the markers were highly polymorphic and reproducible with an average of 8.2 alleles per locus. The markers were used to characterize 54 S. vesicarium isolates from major NY onion production regions in 2016 (n = 27) and 2018 (n = 27). Fifty-two multilocus genotypes (MLGs) were identified between these populations. Genotypic and allelic diversities were high in both the 2016 and 2018 populations. A greater degree of genetic variation was observed within populations than between years. No distinct pattern of MLGs according to population was identified and some MLGs were closely related between 2016 and 2018. The lack of evidence for linkage among loci also was strongly suggestive of clonal populations with only minor differences between the two populations. These microsatellite markers will be a foundational resource for the testing of hypotheses surrounding the population biology of S. vesicarium and therefore informing disease management.

Sampling, a New iOS Application for Assessment of Damage by Diseases and Insect Pests Using Sequential Sampling Plans.

Regular scouting for plant diseases and insect pests by growers, crop consultants, extension educators, and researchers (herein defined as stakeholders) is the cornerstone of integrated pest management practices. Sequential sampling plans have the potential to save time and labor in field scouting and reduce the frequency of errors surrounding decision-making. The incorporation of the algorithms behind sequential sampling plans into mobile devices can make scouting for diseases and insect pests more straightforward, practical, and enjoyable. Here, we introduce an iOS application called Sampling. The application was designed for stakeholders to use on a mobile device for assessing disease and insect pest incidence in the field using sequential sampling plans. The application allows users to select a disease or insect pest from a prepopulated list and specify the objective of sampling: Estimation or classification. Conducting sequential sampling depends upon different precision levels and action thresholds within each objective. Detailed instructions for each sequential sampling plan are available as a guide. When sampling begins, users enter the number of diseased individuals at each sampling unit. The specific algorithm developed for the disease or insect pest will inform the user when to stop sampling for the desired goal and return the final incidence and precision or threshold achieved. Results are automatically saved in the application, and the user can inspect and share results by exporting them to a range of compatible programs. The initial version of Sampling (1.1) was released with the sequential sampling plans for Cercospora leaf spot of table beet. Sequential sampling plans for additional diseases or pests will be added to Sampling in subsequent versions. Sampling is available as a free download from the Apple Store (https://apple.co/3pUiYKy) and is compatible with iOS 14.0 or greater on the iPhone or iPad.

The Population of Fusarium oxysporum f. sp. cubense in Brazil Is Not Structured by Vegetative Compatibility Group or by Geographic Origin.

Fusarium wilt, caused by the soilborne fungus Fusarium oxysporum f. sp. cubense (Foc), is considered one of the most destructive diseases of bananas in Brazil. In this study, a collection of 194 monosporic isolates from several banana-producing regions located in different climatic zones along a south-to-north transect in Brazil was formed to assess the genetic structure of the population of Foc. The isolates underwent pathogenicity tests, PCR diagnosis for the detection of tropical race 4, and screening of SIX homolog genes that produce putative effector proteins. The vegetative compatibility group (VCG) of 119 isolates was determined by pairing against 17 internationally known VCG-tester strains. A group of 158 isolates was selected for simple sequence repeat (SSR) genotyping. There was moderate diversity of Foc in Brazil. Eight VCGs were identified: 0120, 0122, 0124, 0125, 0128, 01215, 01220, and 01222, of which 78% of isolates belong to a single VCG, whereas 22% of isolates are assigned to multiple VCGs, belonging to complexes of VCGs. The distribution of VCGs is uneven and independent of the banana genotype. The isolates of a VCG shared a similar profile of SIX homologs, but there was no association with geographic region. Four SSR loci were polymorphic, and, on average, 7.5 alleles were detected per locus. Thirty-five multilocus genotypes (MLGs) were identified. There was no association between VCG and MLGs, and no genetic structure of the population of Foc in Brazil was detected.

Spatiotemporal Dynamics of Stemphylium Leaf Blight and Potential Inoculum Sources in New York Onion Fields.

Stemphylium leaf blight (SLB) caused by Stemphylium vesicarium is the dominant foliar disease affecting large-scale onion production in New York. The disease is managed by fungicides, but control failures are prevalent and are attributed to fungicide resistance. Little is known of the relative role of inoculum sources in initiation and spread of SLB epidemics. Plate testing of 28 commercially available organic onion seedlots from 2016 and 2017 did not detect S. vesicarium. This finding suggests that although S. vesicarium has been reported as seed-transmitted, this is unlikely to be a significant inoculum source in commercially available organic seed lots and even less so in fungicide-treated seed used to establish conventional fields. The spatial and spatiotemporal dynamics of SLB epidemics in six onion fields were evaluated along linear transects in 2017 and 2018. Average SLB incidence increased from 0 to 100% throughout the cropping seasons with an average final lesion length of 28.3 cm. Disease progress was typical of a polycyclic epidemic and the logistic model provided the best fit to 83.3% of the datasets. Spatial patterns were better described by the beta-binomial than binomial distribution in half of the datasets (50%) and random patterns were more frequently observed by the index of dispersion (59%). Geostatistical analyses also found a low frequency of datasets with aggregation (60%). Spatiotemporal analysis of epidemics detected that the aggregation was influenced by disease incidence. However, diseased units were not frequently associated with the previous time period according to the spatiotemporal association function of spatial analyses by distance indices. Variable spatial patterns suggested mixed inoculum sources dependent upon location, and likely an external inoculum source at the sampling scale used in this study. A small-plot replicated trial was also conducted in each of 2 years to quantify the effect of S. vesicarium-infested onion residue on SLB epidemics in a field isolated from other onion fields. SLB incidence was significantly reduced in plots without residue compared with those in which residue remained on the soil surface. Burial of infested residue also significantly reduced epidemic progress in 1 year. The effect of infested onion residue on SLB epidemics in the subsequent onion crop suggests rotation or residue management may have a substantial effect on epidemics. However, the presence of an inoculum source external to fields in onion production regions, as indicated by a lack of spatial aggregation, may reduce the efficacy of in-field management techniques.

Sensitive attitudes and adherence to recommendations during the COVID-19 pandemic: Comparing direct and indirect questioning techniques.

During the COVID-19 pandemic, various behavioral measures were imposed to curb the spread of the virus. In a preregistered study based on a quota-representative sample of adult Danish citizens (N = 1031), we compared the prevalence estimates of self-reported handwashing, physical distancing, and attitudes toward the behavioral measures between people surveyed with a direct and an indirect questioning approach (i.e., the crosswise model). Moreover, we investigated two possible predictors of sensitive behaviors and attitudes, namely empathy for people vulnerable to the virus and Honesty-Humility from the HEXACO Model of Personality. We also examined the interaction of both predictors with the questioning format. Survey participants reported more violation of guidelines regarding handwashing and physical distancing when asked indirectly rather than directly, whereas attitudes regarding the behavioral measures did not differ between the two questioning formats. Respondents with less empathy for people vulnerable to COVID-19 reported more violations of handwashing and physical-distancing, and those low on Honesty-Humility reported more violations of physical distancing.

Development of a Sequential Sampling Plan using Spatial Attributes of Cercospora Leaf Spot Epidemics of Table Beet in New York.

Sampling strategies that effectively assess disease intensity in the field are important to underpin management decisions. To develop a sequential sampling plan for the incidence of Cercospora leaf spot (CLS), caused by Cercospora beticola, 31 table beet fields were assessed in the state of New York. Assessments of CLS incidence were performed in six leaves arbitrarily selected in 51 sampling locations along each of three to six linear transects per field. Spatial pattern analyses were performed, and results were used to develop sequential sampling estimation and classification models. CLS incidence (p) ranged from 0.13 to 0.92 with a median of 0.31, and beta-binomial distribution, which is reflective of aggregation, best described the spatial patterns observed. Aggregation was commonly detected (>95%) by methods using the point-process approach, runs analyses, and autocorrelation up to the fourth spatial lag. For Spatial Analysis by Distance Indices, or SADIE, 45% of the datasets were classified as a random pattern. In the sequential sampling estimation and classification models, disease units are sampled until a prespecified target is achieved. For estimation, the goal was sampling CLS incidence with a preselected coefficient of variation (C). Achieving the C = 0.1 was challenging with <51 sampling units, and only observed on datasets with incidence >0.3. Reducing the level of precision, i.e., increasing C to 0.2, allowed the preselected C to be achieved with a lower number of sampling units and with an estimated incidence ([Formula: see text]) close to the true value of p. For classification, the goal was to classify the datasets above or below prespecified thresholds (pt) used for CLS management. The average sample number, or ASN, was determined by Monte Carlo simulations, and was between 20 and 45 at disease incidence values close to pt, and approximately 11 when far from pt. Correct decisions occurred in >76% of the validation datasets. Results indicated these sequential sampling plans can be used to effectively assess CLS incidence in table beet fields.