Hypothesis Testing Approach Research Articles

Two-Stage Optimal Hypotheses Testing for a Model of Stegosystem with an Active Adversary

We study the information-theoretic model of stegosystem with an active adversary, where unlike a passive adversary he can not only read but also write. The legitimate sender as well as the adversary can embed or not a message in the sending data. The receiver’s first task is to decide whether the communication is a covertext, data with no hidden message, or a stegotext, modified data with a hidden secret message. In case of stegotext, the receiver’s second task is to decide whether the message was sent by a legitimate sender or from an adversary. For this purpose an authenticated encryption from the legitimate sender is considered. In this paper we suggest two-stage statistical hypothesis testing approach from the receivers point of view. We propose the logarithmically asymptotically optimal testing for this model. As a result the functional dependence of reliabilities of the first and second kind of errors in both stages is constructed. A comparison of overall error probabilities with the situation of one stage hypotheses testing is discussed and the behaviour of functional dependences of reliabilities are illustrated.

Take a Chance on Me: Aleatory Poetry, Generative AI, and the External Demarcation Problem

Abstract What is it in virtue of which any poetic output will be included or excluded from the category of art? I will first identify the external demarcation problem, which is concerned with whether or how the cut-off is made between art and non-art. I will then adopt a nonclassical approach to conceptual analysis by relying on a set of examples of poetry generated by aleatory processes to evaluate an intention-based response to the external demarcation problem. I will argue in favor of an intention-based response that is grounded in hypothetical intentionalism. According to this response, a contextually informed audience will form a hypothesis about poetic intentions on the basis of the evidence that a work makes publicly available. Semantic, categorial, and ostensive intention and intention traces may help this audience to determine whether a work counts as art and is worth effortful interpretation. My proposed version of an intention-based response to the external demarcation problem will be based on the p-valued hypothesis-testing approach in science and will be highly relevant to a context of production in which we find human poets, poetry-generating AI systems, and human-AI interfaces.

The Development of a Concept Test for “Pure Matter and Mixtures” Unit

The purpose of this study was to create a concept test with established reliability and validity to show seventh-grade students’ conceptual comprehension of the science course’s “Pure Matter and Mixtures” unit. The survey model, which is one of the quantitative research methodologies, was used to perform the research. The research group comprises 7th (n=272) and 8th (n=282) grade pupils studying in Ankara province’s Çankaya and Yenimahalle districts throughout the autumn and spring semesters of the 2021-2022 academic year. The first stage of the test questions was multiple-choice with four possibilities, and the second stage was open-ended with the rationale for the question written. Expert comments were sought to guarantee the test’s face and content validity. The hypothesis testing approach was employed to assess construct validity, and the test was found to be construct-valid. As a consequence of the analysis performed before the pilot deployment for the 35-question exam, 9 questions were deleted from the test, yielding a 26-question test. The discrimination of question 21 was discovered to be 0,27 as a result of the test’s actual implementation. The decision was made to delete this question from the tests, and the test was completed with 25 questions. The actual implementation resulted in a KR-20 reliability coefficient of 0,83, a mean item difficulty of 0,56, and a mean item discrimination of 0,49. In light of the results of the present research, a high discrimination, medium difficulty, and reliable concept exam consisting of 25 questions was developed to measure conceptual understanding as well as misconceptions.

A Hypothesis testing approach to Zero-Fault-Shot learning for Damage Component Classification

Often, in condition monitoring, datasets are asymmetric. That is, for most machines being monitored, there is no labeled fault data, only nominal data (hence, the dataset is asymmetric). Deep Learning and other neural network-based mechanization have difficulty solving this type of problem, as they typically require a full set of labeled data, both nominal and faulted. Zero-Fault Shot learning is a class of machine learning problems with no labeled fault training data. In this class of problems, only nominal data is used for knowledge transfer. In this paper, a mixed hypothesis testing and Bayes classifier it used to provide both inferences to the type of fault and also provide information as to when maintenance should be provided. This is done without any fault data and demonstrates knowledge transfer from a set of nominal components, greatly reducing the cost of implementation and fielding of a system.

Testing the missing at random assumption in generalized linear models in the presence of instrumental variables.

Practical problems with missing data are common, and many methods have been developed concerning the validity and/or efficiency of statistical procedures. On a central focus, there have been longstanding interests on the mechanism governing data missingness, and correctly deciding the appropriate mechanism is crucially relevant for conducting proper practical investigations. In this paper, we present a new hypothesis testing approach for deciding between the conventional notions of missing at random and missing not at random in generalized linear models in the presence of instrumental variables. The foundational idea is to develop appropriate discrepancy measures between estimators whose properties significantly differ only when missing at random does not hold. We show that our testing approach achieves an objective data-oriented choice between missing at random or not. We demonstrate the feasibility, validity, and efficacy of the new test by theoretical analysis, simulation studies, and a real data analysis.

Role of Supply Chain Management in Quality of Healthcare Services

Healthcare organizations in Haryana (Kurukshetra) face many supply chain management challenges that can be addressed through effective operational and management decisions. The aim of this paper is to examine the supply chain management of healthcare quality in developing countries, particularly in rural healthcare in Haryana (Kurukshetra), and to consider demographic variables such as gender, age, education level and healthcare experience. Design and Hypothesis Testing Approach Distributed 500 questionnaires to determine the impact of aspects of supply chain management on the quality of health services. 27 of his seven procurement officers and administrative staff in Kurukshetra Haryana. The primary method was to collect data from 73 rural health managers and procurement managers to identify the quality and size of health services. The results of our study show that a combination of timely delivery of health products, specifications, level of health product providers and safety in the rural health sector of Haryana (Kurukshetra) is related to the quality of health services. The scope of this article focuses on employing appropriate human resources and highly trained professionals in supply chain departments to improve the quality of health services in the supply chain. As a practical contribution, this article can help healthcare supply chain managers and organizations do their jobs better or create a competitive advantage by addressing the issues and challenges facing individual healthcare managers, organizations and their partners.

Validity of the trunk assessment scale for spinal cord injury (TASS) and the trunk control test in individuals with spinal cord injury

Background The Trunk Assessment Scale for Spinal Cord Injury (TASS) and the Trunk Control Test for individuals with a Spinal Cord Injury (TCT-SCI) are highly reliable assessment tools for evaluating the trunk function of individuals with SCIs. However, the potential differences in the validity of these two scales are unclear. Objectives To evaluate the criterion validity of the TASS and the construct validity of the TASS and TCT-SCI. Participants and Methods We evaluated 30 individuals with SCIs (age 63.8 ± 10.7 yrs, 17 with tetraplegia). To evaluate criterion validity, we calculated Spearman's rho between the TASS and the gold standard (the TCT-SCI). To determine construct validity, we used the following hypothesis testing approaches: (i) calculating Spearman's rho between each scale and the upper and lower extremity motor scores (UEMS, LEMS), the Walking Index for SCI-II (WISCI-II), and the motor score of the Functional Independence Measure (mFIM); and (ii) determining the cut-off point for identifying ambulators with SCIs (≥ 3 points on item 12 of Spinal Cord Independent Measure III) by a receiver operating characteristics analysis. Results A moderate correlation was confirmed between the TASS and the TCT-SCI (r = 0.68). Construct validity was supported by six of the eight prior hypotheses. The cut-off points for identifying ambulators with SCIs were 26 points (TASS) and 18 points (TCT-SCI). Conclusion Our results indicate that the contents of the TASS and the TCT-SCI might reflect the epidemiological characteristics of the populations in which they were developed.

Responsiveness of the Patient-Reported Outcome Measure-Haemorrhoidal Impact and Satisfaction Score in patients with haemorrhoidal disease.

In this study we aimed to assess the responsiveness of the symptom score of the recently developed Patient-Reported Outcome Measure-Haemorrhoidal Impact and Satisfaction Score (PROM-HISS). Furthermore, the minimally relevant difference (MRD) was determined. The responsiveness of PROM-HISS was tested using a criterion-based (i.e. anchor) and construct-based (i.e. hypotheses testing) approach. Patients with haemorrhoidal disease (HD) completed the PROM-HISS before and 1 week after treatment in hospital. A global self-assessment of change question (SCQ) was administered 1-week after treatment and functioned as the criterion. The following analyses were performed: (1) correlation between the PROM-HISS symptom score and the criterion (SCQ) and (2) hypotheses testing. The MRD was determined as change in symptoms of the subgroup reporting 'somewhat fewer complaints' on the SCQ. Between February and August 2022, 94 patients with grade II-IV HD from three hospitals were included. The correlation between the SCQ and a change on the PROM-HISS symptom score was 0.595 indicating that an improvement on the SCQ corresponds to an improvement on the PROM-HISS symptom score. As hypothesized, the mean change in PROM-HISS scores was significantly different between subgroups of patients based on their SCQ responses. Patients reporting a small change in HD symptoms on the SCQ corresponded to a mean change of 0.3 on the PROM-HISS symptom score. The PROM-HISS symptom score is a responsive instrument as it identifies change in HD symptoms because of treatment. The estimated MRD of 0.3 can be used to inform clinical research and practice.

Applying a geometric morphometric surface semilandmark-based approach for assessing sexual dimorphism in cranial bones

Traditionally, sex estimation in human skulls has been carried out applying non-metric and inter-landmark distance approaches. Such estimation has substantially improved with the introduction of geometric morphometric semilandmark-based registration, representing a useful tool for capturing the complex morphology of 3D surfaces, particularly in human skulls. Taking in account these improvements, the main purpose of this study is to show the benefits of these techniques for assessing by means of a quantitative, hypothesis testing approach the differential phenotypic expression of sexual dimorphism in human cranial traits, using the frontal bone, the mastoid process of the temporal bone, and the zygomatic bone as proxies. According to our main results: i) accuracy and precision of sex estimation is higher when the shape variable is included in the analysis than when it is not, ii) numerical classification tends to be more accurate in males than in females for both shape and size components of sexual dimorphism, and iii) a single trait or two traits in combination would be more successful in sex classification than the three traits taken as a whole. The introduction in the present study of a surface semilandmark-based approach for quantitatively assessing sexual dimorphism in human skull considerably improves the capture of sexual dimorphic signatures, corroborating the importance of the information carried by the surface of the frontal bone, mastoid process, and zygomatic bone. Our results suggest that shape and size components should be considered as relevant factors in making a differential, bone- dependent sex assessment in human crania.

Significance analysis for clustering with single-cell RNA-sequencing data.

Unsupervised clustering of single-cell RNA-sequencing data enables the identification of distinct cell populations. However, the most widely used clustering algorithms are heuristic and do not formally account for statistical uncertainty. We find that not addressing known sources of variability in a statistically rigorous manner can lead to overconfidence in the discovery of novel cell types. Here we extend a previous method, significance of hierarchical clustering, to propose a model-based hypothesis testing approach that incorporates significance analysis into the clustering algorithm and permits statistical evaluation of clusters as distinct cell populations. We also adapt this approach to permit statistical assessment on the clusters reported by any algorithm. Finally, we extend these approaches to account for batch structure. We benchmarked our approach against popular clustering workflows, demonstrating improved performance. To show practical utility, we applied our approach to the Human Lung Cell Atlas and an atlas of the mouse cerebellar cortex, identifying several cases of over-clustering and recapitulating experimentally validated cell type definitions.

Digital Teaching Competence According to the DigCompEdu Framework. Comparative Study in Different Latin American Universities

The relevance and importance that the topic of Digital Competences for Teachers (DCT) has gained is evident both in the field of training and in research, as can be seen by the increase in the amount of research and meta-analysis carried out on this topic. This article presents the results of an ex post facto research with a cross-sectional research design, based on a descriptive and hypothesis-testing approach. A total of 6,664 teachers from different Latin American universities participated in the self-knowledge they have regarding their Digital Teaching Competence (DTC) according to the DigCompEdu framework of the European Union. Among the results obtained, it is worth noting the intermediate level of digital competences reported by the teachers surveyed, with significant differences with respect to different key variables for their development. Therefore, we conclude by reflecting on the need to establish teacher training plans in this area.

The Evaluation of The Performance of MSMEs Leaders in Mandailing Natal Regency

This study examines the relationship between servant leadership, innovativeness, competence, and leadership performance in Micro, Small, and Medium Enterprises (MSMEs) in Mandailing Natal regency. The research aims to determine the significance of these variables and their impact on MSMEs' leadership effectiveness. The study employed a hypothesis testing approach, using a significance level of 0.05, to analyze the collected data. The results revealed that servant leadership, as indicated by a p-value of 0.007, innovativeness (p-value of 0.000), and competence (p-value of 0.000) significantly influenced the performance of MSMEs leaders. The findings suggest that leaders who prioritize serving others, demonstrate innovative thinking, and possess the necessary competencies are associated with improved performance in MSMEs leadership roles. The discussion highlights the importance of adopting a service-oriented leadership style, fostering innovation, and investing in leadership competencies to enhance leadership effectiveness in MSMEs. These results have practical implications for MSMEs in Mandailing Natal regency. By embracing servant leadership values, fostering a culture of innovation, and developing leadership competencies, MSMEs can improve their overall performance, operational efficiency, and strategic decision-making. It is important to note that these findings are specific to the context of MSMEs in Mandailing Natal regency. Further research in different settings and industries would contribute to a broader understanding of the relationship between these variables.

Scalable Change Analysis and Representation Using Characteristic Function

In this paper, we propose a novel framework to help human operators- who are domain experts but not necessarily familiar with statistics- analyze a complex system and find unknown changes and causes. Despite the prevalence, researchers have rarely tackled this problem. Our framework focuses on the representation and explanation of changes occurring between two datasets, specifically the normal data and data with the observed changes. We employ two-dimensional scatter plots which can provide comprehensive representation without requiring statistical knowledge. This helps a human operator to intuitively understand the change and the cause. An analysis to find two-attribute pairs whose scatter plots well explain the change does not require high computational complexity owing to the novel characteristic function-based approach. Although a hyper-parameter needs to be determined, our analysis introduces a novel appropriate prior distribution to determine the proper hyper-parameter automatically. The experimental results show that our method presents the change and the cause with the same accuracy as that of the state-of-the-art kernel hypothesis testing approaches, while reducing the computational costs by almost 99% at the maximum for all popular benchmark datasets. The experiment using real vehicle driving data demonstrates the practicality of our framework.

TROPHY-U-01 Cohort 4 (C4): Sacituzumab govitecan (SG) in combination with cisplatin (cis) as first-line (1L) therapy, followed by maintenance avelumab plus (+) SG or zimberelimab (zim) + SG in patients (pts) with treatment (Tx)-naïve metastatic urothelial cancer (mUC).

TPS4611 Background: SG is a Trop-2–directed antibody-drug conjugate. In the TROPHY-U-01 study, SG monotherapy showed a 27% objective response rate (ORR) and 10.9 months median overall survival (OS) with an overall manageable safety profile in pts with mUC who received platinum (PT)-containing chemotherapy and a checkpoint inhibitor (CPI), resulting in accelerated FDA approval in this population. PT-based chemotherapy followed by avelumab maintenance is standard 1L therapy in pts with Tx-naïve mUC. Zim (anti–PD-1) is a CPI under clinical investigation for antitumor activity. C4 of TROPHY-U-01 will evaluate safety, tolerability, and clinical activity of SG+cis followed by maintenance avelumab+SG or zim+SG in cis-eligible pts with Tx-naïve mUC. Methods: TROPHY-U-01 (NCT03547973) is a multicohort, open-label, global, phase 2 study. C4 will evaluate 1L SG in combination with cis in pts with cis-eligible mUC or unresectable locally advanced disease. Eligibility requirements include ECOG PS 0-1; no prior anticancer monoclonal antibody within 4 weeks of study drug initiation; no history of active interstitial lung disease or noninfectious pneumonitis; adequate hematologic and hepatic function. Pts will be treated with cis at 70 mg/m2 on D1 of 21-D cycles (if creatinine clearance [CrCl] ≥60 mL/min) or at an optional split dose of 35 mg/m2 on D1 and D8 of 21-D cycles (if CrCl 50-59 mL/min), followed by SG (5, 7.5, or 10 mg/kg, based on 10-pt safety lead-in of a 3+3 design) on D1 and D8 of 21-D cycles. Granulocyte colony-stimulating factor support is not allowed in the safety lead-in but was permitted during escalation and expansion. SG+cis will continue for up to 6 cycles, followed by maintenance (4 to 8 wk after last induction dose of SG+cis and when RP2D is determined) in the absence of progression. Dose escalation maintenance consists of avelumab 800 mg q2w, then SG 10 mg/kg on D1 and D8 of 21-D cycles. Dose expansion maintenance consists of zim 360 mg (D1 of a 21-D cycle) and SG 10 mg/kg (D1 and D8 of 21-D cycles) and will begin once safety lead-in of 6-8 pts receiving zim+SG of a 21-D cycle in Cohort 5 is deemed safe and completed. Pts will continue Tx until progression, unacceptable toxicity, or loss of clinical benefit. Primary endpoint is ORR per RECIST v1.1 by central review. Secondary endpoints include progression-free survival, duration of response, and clinical benefit rate per central review and investigator assessment. OS and safety will also be evaluated. All statistical analyses will be performed using a two-sided hypothesis test approach at the overall 5% level of significance. Time to event endpoints will be assessed via the Kaplan-Meier method. Enrollment is ongoing; up to 57 pts expected across ~120 sites in North America and Europe. Clinical trial information: NCT03547973 .

A Bayesian approach to study design and analysis with type I error rate control for response variables of mixed types.

There has been increased interest in the design and analysis of studies consisting of multiple response variables of mixed types. For example, in clinical trials, it is desirable to establish efficacy for a treatment effect in primary and secondary outcomes. In this article, we develop Bayesian approaches for hypothesis testing and study planning for data consisting of multiple response variables of mixed types with covariates. We assume that the responses are correlated via a Gaussian copula, and that the model for each response is, marginally, a generalized linear model (GLM). Taking a fully Bayesian approach, the proposed method enables inference based on the joint posterior distribution of the parameters. Under some mild conditions, we show that the joint distribution of the posterior probabilities under any Bayesian analysis converges to a Gaussian copula distribution as the sample size tends to infinity. Using this result, we develop an approach to control the type I error rate under multiple testing. Simulation results indicate that the method is more powerful than conducting marginal regression models and correcting for multiplicity using the Bonferroni-Holm Method. We also develop a Bayesian approach to sample size determination in the presence of response variables of mixed types, extending the concept of probability of success (POS) to multiple response variables of mixed types.

The Screen for Cognitive Impairment in Psychiatry (German version, SCIP-G): Validation, dimensionality analysis and practical application in inpatient psychiatric treatment

IntroductionPsychiatric disorders are often characterised by cognitive impairment. The Screen for Cognitive Impairment in Psychiatry (SCIP) was developed for routine screening of psychiatric patients and is available in several languages.ObjectivesUsing the German version (SCIP-G), 3 studies were conducted: 1. feasibility, reliability, and validity of the SCIP-G were investigated [Sachs et al. Schizophr. Res. Cogn. 2021: 25, 100197], 2. a confirmatory factor analysis was performed [Sachs et al. Schizophr. Res. Cogn. 2022: 29, 100259], and 3. patients with psychotic, bipolar affective, and depressive disorders were assessed before and after standard inpatient treatment including cognitive remediation.MethodsStudy 1 included patients with schizophrenia or schizoaffective psychosis and thirty healthy controls matched for sex, age, and education. Data were collected at the Medical University of Vienna, Department of Psychiatry and Psychotherapy. In studies 2 and 3, patients from the Klinik Hietzing, 1st Department of Psychiatry and Psychotherapeutic Medicine, Vienna, Austria, were studied. In study 3, all patients received modern pharmacotherapy plus cognitive remediation using the COGPACK® software package version 6.06; based on the ICD-10 criteria for research, 54 patients received an F2 diagnosis (schizophrenia, schizotypal, and delusional disorders), 39 patients met criteria for bipolar disorder (F30 and F31), and 50 for depression (F32 and F33).ResultsIn Study 1, significant differences in cognitive performance were found between patients and healthy controls on both versions of the SCIP. The SCIP effectively discriminated between patients and the control group. In Study 2, a two-factor solution in which the Verbal Learning Test-Immediate Recall subtests, Delayed Recall Test of the VLT, and Working Memory Test loaded on the first factor and the Verbal Fluency Test and Psychomotor Speed Test subtests loaded on the second factor yielded good model fit (χ² = 6.7, df = 3, p = .08, χ²/df = 2.2). In Study 3, SCIP total score showed significant improvement after treatment in all three diagnostic groups (p < .001), with no statistically significant interaction between SCIP total score and diagnostic groups (p = .860).ConclusionsOur data indicate that the SCIP-G is a valid and reliable instrument for assessing cognitive impairment. Good model fit can be achieved with a two-factor solution for the SCIP. Our study is the first to perform a confirmatory factor analysis with the German SCIP version and to test its dimensional structure with a hypothesis-testing approach. Inpatient treatment consisting of pharmacotherapy and cognitive remediation improved cognitive deficits. This improvement in cognitive performance was observed to a similar extent in patients with psychotic disorders, bipolar disorder, and depression.Disclosure of InterestNone Declared

Marketing Communication Tools, Emotional Connection, and Brand Choice: Evidence from Healthy Food Industry

This research examines the effects of information sharing, peer pressure, and entertainment on attitude towards a brand. In addition, this research also examines the effects of entertainment on emotional connection, emotional connection on purchase intention, and attitude towards a brand on purchase intention. This research uses SEM (Structural Equation Modelling) method and LISREL version 8.80 as tools for data analysis. The population is people in the city of Jakarta. The number of respondents in this research amounts to 165 people. The respondents taken in this research are those familiar with healthy food of FMCG (Fast Moving Consumer Goods) type and have seen healthy food advertisements on social media. Then, this study uses quantitative methods and a hypothesis-testing approach. Firstly, information sharing has no significant effect on attitude towards a brand, unlike peer pressure having a significant effect on attitude towards a brand. Furthermore, entertainment also considerably affects the attitude towards a brand as much as it does emotional connection. Finally, attitude towards a brand has a significant effect on purchase intention. The research findings indicate that peer pressure and entertainment influence the attitude toward a brand, while information sharing does not significantly influence the attitude toward a brand. The effects of entertainment on emotional connection, emotional connection on purchase intention, and attitude towards a brand on purchase intention are significant. To reinforce purchase intention, it is suggested that entertainment and emotional marketing be maximally utilized due to the amount of influence these could generate.

Comparison of Information Criteria for Detection of Useful Signals in Noisy Environments.

This paper considers the appearance of indications of useful acoustic signals in the signal/noise mixture. Various information characteristics (information entropy, Jensen-Shannon divergence, spectral information divergence and statistical complexity) are investigated in the context of solving this problem. Both time and frequency domains are studied for the calculation of information entropy. The effectiveness of statistical complexity is shown in comparison with other information metrics for different signal-to-noise ratios. Two different approaches for statistical complexity calculations are also compared. In addition, analytical formulas for complexity and disequilibrium are obtained using entropy variation in the case of signal spectral distribution. The connection between the statistical complexity criterion and the Neyman-Pearson approach for hypothesis testing is discussed. The effectiveness of the proposed approach is shown for different types of acoustic signals and noise models, including colored noises, and different signal-to-noise ratios, especially when the estimation of additional noise characteristics is impossible.

Reinforcing Data Integrity in Renewable Hybrid AC-DC Microgrids from Social-Economic Perspectives

The microgrid (MG) is a complicated cyber-physical system that operates based on interactions between physical processes and computational components, which make it vulnerable to varied cyber-attacks. In this article, the impact of data integrity attack (DIA) has been considered, as one of the most dangerous cyber threats to MGs, on the steady-state operation of hybrid microgrids (HMGs). Additionally, a novel method based on the sequential hypothesis testing approach is proposed to detect DIA on the renewable energy sources’ metering infrastructure and improve the data security within the HMGs. The proposed method generates a binary sample, which is used to compute a test statistic that is further used against two thresholds to decide among three alternatives. The performance of the suggested method is examined using an IEEE standard test system. The results illustrated the acceptable performance of the proposed methodology in detection of DIAs. In addition, to evaluate the effect of DIA on the operation of the HMGs, DIAs with different severities are launched on the measured power generation of renewable energy resources like wind turbines. The results showed that a successful DIA on renewable units can severely affect the operation of electric grids and cause serious damage.

Objective Bayesian Approach for Binary Hypothesis Testing of Multivariate Gaussian Observations

This paper proposes an objective Bayesian detector for the binary hypothesis testing problem in which the observation vectors are IID and follow multivariate Gaussian distribution under both the null and alternative hypotheses. The mean vector and covariance matrix under each hypothesis are not known, they also do not have special structure other than the covariance matrices are partially ordered in the positive definite cone with their difference positive semi-definite. An example of such a problem is the detection of Gaussian random signal in Gaussian noise. Non-informative priors are imposed on the unknown parameters for computing the marginals and evaluating the Bayes factor test statistic, where the prior for the covariance matrix is applied to the Cholesky factorization of the precision matrix. For the null hypothesis, we propose conjugate priors for the unknowns. For the alternative hypothesis, we propose uniform prior on the mean vector, and a class of objective priors that encompasses the Jeffreys, Independence Jeffreys, Geisser and Cornfield, Haar Measure and Reference priors for the precision matrix. The proposed priors enable closed-form expressions for the marginals and lead to an objective Bayes factor having the posteriors mainly governed by the data. The proposed detector is analyzed for justifying the priors used, deriving the theoretical moments, and approximating the false alarm and detection probability densities by the shifted Gamma distributions. The developed detector exhibits improvement in detection performance over the energy detector (ED) and the generalized likelihood ratio test (GLRT).