scholarly journals ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI AUDIT DELAY

2021 ◽  
Vol 6 (01) ◽  
pp. 19-33
Author(s):  
Maulina Dyah Permatasari ◽  
Muhammad Mahessa Saputra
Keyword(s):  

Setiap perusahaan yang tercatat di Bursa Efek Indonesia harus melaporkan laporan keuangannya kepada Otoritas Jasa Keuangan (OJK) setelah diaudit oleh auditor eksternal. Jika terlambat, maka akan dikenakan sanksi. Audit delay adalah lamanya waktu untuk menyelesaikan proses audit dari akhir tahun fiskal hingga tanggal diterbitkannya laporan audit. Tujuan penelitian ini adalah untuk mengetahui pengaruh pergantian auditor, reputasi KAP, opini audit dan komite audit terhadap audit delay pada perusahaan jasa transportasi yang terdaftar di Bursa Efek Indonesia tahun 2016-2019. Populasi penelitian ini adalah perusahaan jasa transportasi yang terdaftar di BEI tahun 2016–2019 sebanyak 45 perusahaan dengan teknik pengambilan sampel yaitu puposive sampling dan menghasilkan 27 perusahaan untuk diuji. Teknik analisis yang digunakan adalah analisis logistik. Hasil penelitian menunjukkan bahwa (1) pergantian auditor tidak berpengaruh terhadap audit delay dengan nilai β 0,089 dan nilai signifikansinya 0,875, (2) reputasi auditor tidak berpengaruh terhadap audit delay dengan nilai β -0,512 dan nilai signifikansinya 0,420, (3) opini audit berpengaruh negatif signifikan terhadap audit delay dengan nilai β -1.992 dan nilai signifikansinya 0,004, (4) komite audit tidak berpengaruh terhadap audit delay dengan nilai β 0,098 dan nilai signifikansinya 0,776, (5) Hasil uji simultan pada analisis ini menggunakan Omnibus Test yang menunjukkan bahwa semua variabel secara simultan berpengaruh signifikan terhadap audit delay dengan nilai signifikansinya 0,046.

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1222.1-1222
Author(s):  
L. Joos ◽  
S. Gonzalez Chiappe ◽  
T. Neumann ◽  
A. Mahr

Background:Co-prescribing 2-mercaptoethane sodium sulfonate (mesna) with cyclophosphamide (CYC) for ANCA-associated vasculitis (AAV) aims to prevent the potential urotoxic effects of CYC. The evidence for this practice is often considered weak, and there may be some diversity in what practitioners do in clinical practice.Objectives:To investigate current clinical practice related to prescribing mesna prophylaxis or not and the underlying rationale for CYC-treated patients with AAV.Methods:We searched MEDLINE for publications with the MeSH term “ANCA-associated vasculitis” over a 10-year period up to October 2020. Email addresses of authors of these publications were extracted from the online information available in MEDLINE. These authors were invited by email to participate in an anonymous online SurveyMonkey survey of 21 to 24 questions asking about the characteristics of the respondent, their experience with AAV, and their practice in using CYC to treat AAV and using mesna in CYC-treated patients with AAV and the underlying rationale. Respondents were eligible to take the full survey if they were involved in deciding and/or monitoring therapy with CYC for patients with AAV. We compared 15 response variables to identify factors associated with the use or not of mesna. Response variables with multiple categories were first analyzed across all categories; if the omnibus test result was significant, additional analyses were used to identify the categories, which were the sources of group separation. We analyzed by-country variations for only countries with ≥ 10 respondents. Statistical analyses involved Pearson’s chi-square test or Fisher’s exact test, as appropriate. For multiple-response variables, the Rao-Scott correction was applied.Results:The invitation for the electronic survey was emailed twice in October 2020 to 1,374 unique email addresses; 156 individuals responded; 139 were eligible and completed the survey. The 139 participants were from 34 countries and were essentially MDs (98%) who mainly worked in rheumatology (50%), nephrology (25%) or internal medicine/clinical immunology (18%). Mesna was given in conjunction with CYC systematically, never, or on a case-by-case basis by 68%, 19% and 13% of respondents, respectively. As compared with systematic mesna-prescribers, never/occasional mesna-prescribers reported a longer time since receiving their degree as a health professional (≥ 15 years: 80% vs 50%, P<0.001), were more frequently based in England/United States (than in France/Germany/Italy) (78% vs 21%, P<0.001), had longer involvement in care of patients with AAV (≥ 15 years: 62% vs 37%, P=0.006), had less practice in using intermittent pulse therapy as the exclusive/predominant CYC administration scheme (62% vs 89%, P<0.001), and, as a rationale underpinning their mesna practice, had less adherence to local operational procedures (47% vs 73%, P=0.002) or (inter)national management guidelines for AAV (16% vs 49%, P<0.001). Never/occasional versus systematic use of mesna did not differ across medical specialties (5 categories, P=0.192) or healthcare settings (3 categories, P=0.437), and was not associated with prior experience of CYC-related urotoxic events (3 categories, P=0.495) or severe mesna toxicity issues (3 categories, P=0.957). The confidence that their practice reflected the best possible patient care did not differ between never/occasional and systematic mesna-prescribers (7-point Likert scale, P=0.794).Conclusion:Practice with regard to prescribing mesna in conjunction with CYC to treat AAV is heterogeneous, although systematic mesna use prevailed over never or occasional use. The decision to prescribe or not mesna may be based more on circumstantial than structural reasons.Disclosure of Interests:Lukas Joos: None declared, Solange Gonzalez Chiappe: None declared, Thomas Neumann Speakers bureau: GSK, Grant/research support from: Xifor, Alfred Mahr Speakers bureau: Amgen, Celgene, Roche, Chugai, Consultant of: Amgen, Celgene, Roche, Chugai


2017 ◽  
Vol 1 (02) ◽  
pp. E98-E106
Author(s):  
Bernhard Fehlmann ◽  
Hennric Jokeit

Abstract Background With the Stroop-Interference-NoGo-Test (STING), we introduce an efficient and sensitive screening tool for the assessment of mild to moderate cognitive impairment. Its development was motivated by the ongoing economization of diagnostics and therapy in clinics as well as by the increased recognition of the effects of cognitive impairments on quality of life and professional reintegration. Established screenings such as the MoCA, MMSE and CAMCOG are either more time-consuming or lack sensitivity with regard to mild to moderate impairments in relevant domains. Methods STING is based on the idea of an omnibus test. It integrates attentional, lexical-semantic, speed- and inhibitory components. In this way, a basic sensorimotor component is separated from a higher-order cognitive/executive component, which allows for differentiation between cognitive and generalised or merely sensorimotor impairments. The norms are based on data from 907 participants (386 M, 521 F). Its discriminative power was investigated in 64 patients (32 M, 32 F) with heterogeneous, but predominantly mild to moderate neuropsychological impairments. Results The split-half reliability is essentially r=0.82–0.95. For the parallel-test reliability, the index is r=0.82–0.91, whereas the test-retest stability is estimated somewhat lower (r=0.48–0.81). Practice effects are moderate (7–12%). STING is correlated with many familiar tests, but sets itself apart from mere intelligence testing. Within the age category of 12–34 years, the number of correct items in the more complex second half of the test was predictive for clinical caseness, with a sensitivity of 83% and a specificity of 47%. Between the ages of 35 and 64, the classification was improved by the combination with the ratio of both halves, which represents set-shifting costs. Here the sensitivity of 71% goes hand in hand with a specificity of 70%. Discussion STING provides a measure that can be considered sufficiently sensitive for use in the global assessment of cognitive impairment. A positive result does not replace a neuropsychological assessment, but indicates the need for one. The test offers an opportunity to neurologists, psychologists and psychiatrists to objectify mild to moderate, transient, or chronic functional impairments and to evaluate their course over time.


2010 ◽  
Vol 18 (6) ◽  
pp. 720-725 ◽  
Author(s):  
Jessica Lasky-Su ◽  
Amy Murphy ◽  
Matthew B McQueen ◽  
Scott Weiss ◽  
Christoph Lange

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1508 ◽  
Author(s):  
Jinqi Zhao ◽  
Yonglei Chang ◽  
Jie Yang ◽  
Yufen Niu ◽  
Zhong Lu ◽  
...  

Unsupervised change detection approaches, which are relatively straightforward and easy to implement and interpret, and which require no human intervention, are widely used in change detection. Polarimetric synthetic aperture radar (PolSAR), which has an all-weather response capability with increased polarimetric information, is a key tool for change detection. However, for PolSAR data, inadequate evaluation of the difference image (DI) map makes the threshold-based algorithms incompatible with the true distribution model, which causes the change detection results to be ineffective and inaccurate. In this paper, to solve these problems, we focus on the generation of the DI map and the selection of the optimal threshold. An omnibus test statistic is used to generate the DI map from multi-temporal PolSAR images, and an improved Kittler and Illingworth algorithm based on either Weibull or gamma distribution is used to obtain the optimal threshold for generating the change detection map. Multi-temporal PolSAR data obtained by the Radarsat-2 sensor over Wuhan in China are used to verify the efficiency of the proposed method. The experimental results using our approach obtained the best performance in East Lake and Yanxi Lake regions with false alarm rates of 1.59% and 1.80%, total errors of 2.73% and 4.33%, overall accuracy of 97.27% and 95.67%, and Kappa coefficients of 0.6486 and 0.6275, respectively. Our results demonstrated that the proposed method is more suitable than the other compared methods for multi-temporal PolSAR data, and it can obtain both effective and accurate results.


2018 ◽  
Vol 7 (3.28) ◽  
pp. 68
Author(s):  
Siti Afiqah Muhamad Jamil ◽  
Mohd Asrul Affendi Abdullah ◽  
Kek Sie Long ◽  
Nur Fazilla Mohd Jupri ◽  
Mustafa Mamat

The aims of this study are to fit a logistic regression model towards the fly problem in a farm and to identify the variables that are associated with the fly problem in a poultry farm. By using SPSS software, this study used ‘FORWARD STEPWISE’ and ‘BACKWARD STEPWISE’ methods to perform the analysis. Compared to linear regression analysis, logistic regression does not require rigorous assumptions to be met. This study used Likelihood Ratio test, Omnibus test and Hosmer and Lemeshow test to validate and to test the fit of poultry farm data. Akaike Information Criterion (AIC) is calculated to observe the difference between the methods of stepwise used by SPSS software in this study. As a result, logistic regression is fit towards poultry farm data by a stepwise procedure. BACKWARD STEPWISE seems to be more suitable for conducting the stepwise method of analysis. Besides, variables that influence the problem of fly in a poultry are the wasps, distance and number of flies. 


1993 ◽  
Vol 18 (1) ◽  
pp. 1-40 ◽  
Author(s):  
Robert J. Boik

This article considers two related issues concerning the analysis of interactions in complex linear models. The first issue concerns the omnibus test for interaction. Apparently, it is not well known that the usual F test for interaction can be replaced, in many applications, by a test that is more powerful against a certain class of alternatives. The competing test is based on the maximal product interaction contrast F statistic and achieves its power advantage by focusing solely on product contrasts. The maximal product interaction F test is reviewed and three new results are reported: (a) An extended table of exact critical values is computed, (b) a table of moment functions useful for approximating the p-value corresponding to an observed maximal F statistic is computed, and (c) a simulation study concerning the null distribution of the maximal F statistic when data are unbalanced or covariates are present is reported. It is conjectured that lack of balance or presence of covariates has no effect on the null distribution. The simulation results support the conjecture. The second issue concerns follow-up tests when the omnibus test is significant. It appears that researchers, in general, do not perform coherent follow-up tests on interactions. To make it easier for researchers to do so, an exposition on the use of product interaction contrasts and partial interactions in complex fixed-effects models is provided. The recommended omnibus and follow-up tests are illustrated on an educational data set analyzed using SAS ( SAS Institute, 1988 ) and SPSS (1990) .


1992 ◽  
Vol 17 (1) ◽  
pp. 1-26
Author(s):  
Douglas E. Critchlow ◽  
Joseph S. Verducci

Paired rankings arise when each subject in a study independently ranks a set of items, undergoes a treatment, and afterwards ranks the same set of items. For such data, a statistical test is proposed to detect if the subjects’ posttreatment rankings have moved systematically toward some unknown ranking or set of rankings. The null hypothesis for this test is that each subject’s post-treatment ranking is symmetrically distributed about his pretreatment ranking. The exact and asymptotic null distributions of the test statistic are simulated and compared, and the power of the test is studied. Using paired rankings from an experimental course in literary criticism, we also offer some graphical methods for representing such data that help us to interpret the test results.


Entropy ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. 1294
Author(s):  
Lijuan Huo ◽  
Jin Seo Cho

This study examined the extreme learning machine (ELM) applied to the Wald test statistic for the model specification of the conditional mean, which we call the WELM testing procedure. The omnibus test statistics available in the literature weakly converge to a Gaussian stochastic process under the null that the model is correct, and this makes their application inconvenient. By contrast, the WELM testing procedure is straightforwardly applicable when detecting model misspecification. We applied the WELM testing procedure to the sequential testing procedure formed by a set of polynomial models and estimate an approximate conditional expectation. We then conducted extensive Monte Carlo experiments to evaluate the performance of the sequential WELM testing procedure and verify that it consistently estimates the most parsimonious conditional mean when the set of polynomial models contains a correctly specified model. Otherwise, it consistently rejects all the models in the set.


Stats ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. 56-67
Author(s):  
Dewi Rahardja

In sequential tests, typically a (pairwise) multiple comparison procedure (MCP) is performed after an omnibus test (an overall equality test). In general, when an omnibus test (e.g., overall equality of multiple proportions test) is rejected, then we further conduct a (pairwise) multiple comparisons or MCPs to determine which (e.g., proportions) pairs the significant differences came from. In this article, via likelihood-based approaches, we acquire three confidence intervals (CIs) for comparing each pairwise proportion difference in the presence of over-reported binomial data. Our closed-form algorithm is easy to implement. As a result, for multiple-sample proportions differences, we can easily apply MCP adjustment methods (e.g., Bonferroni, Šidák, and Dunn) to address the multiplicity issue, unlike previous literatures. We illustrate our procedures to a real data example.


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