Simultaneous Hypotheses Research Articles

Simultaneous Hypotheses in Cognitive Agents: Commentary on Paxton, Necaise etal., and the Dynamical Hypothesis in Cognitive Science.

The 1998 article by van Gelder proposed a Dynamical Hypothesis (DH) in cognitive science consisting of Nature (cognitive agents are dynamical systems) and Knowledge (cognitive agents should be understood dynamically) hypotheses in contrast to the Computational Hypothesis (CH) that cognitive agents are computers. My commentary focuses on the contributions of Paxton and Necaise etal. in interpersonal motor coordination and radicalization across social media. I do not think that either contribution supports the Nature hypothesis but does conform with the Knowledge hypothesis. I conclude by describing cognitive agents as living systems (or nonliving systems that mimic aspects of living systems) that can be alternately viewed to support the DH or CH or both at the same time.

The Influences of Content Creation and Community Building on Purchase Decision during COVID-19: A Case Study of Sociolla

This study aims to ascertain the influence of social media marketing via Instagram, which includes content creation and community building, on purchase decision in Sociolla during the pandemic. This study collected primary data from respondents via questionnaires. The respondents were 101 people with customers who became Sociolla followers and made online purchases on Sociolla during the COVID-19 pandemic. SPSS was used to analyze the data in this analysis. Analytical techniques include multiple linear regression analysis, the t test for partial hypotheses, the F test for simultaneous hypotheses, and the coefficient of determination (R²). This study found that content creation and community development had a significant positive effect on purchase decision. The partial results (t test) indicate that the variables relating to content sharing most influence purchase decision. While concurrently (F test) demonstrates that content creation and community building have a significant effect on purchasing decisions. Although the relationship between community building and purchase decision has been examined in past research, the specific relationships examined in this study in comparison with the content creation-purchase decision relationship has not yet been previously investigated using a local cosmetic brand followers in Indonesia.

Effect of Sales Promotion and Trust on Purchase Decisions on the Lazada Marketplace

ABSTRACT
 The purpose of this study is to determine the influence and trustworthiness of purchasing decisions on the Lazada marketplace. The method used in this research is to use verification with a quantitative approach. The sample used in this study was 400 of the total Lazada Indonesia e-commerce visitors. The sampling technique used is non- probability sampling with incidental sampling method. Analysis of the data used is using path analysis with partial and simultaneous hypotheses. The results of this study are that there is a partial influence between Sales Promotion (X1) on Purchase Decisions (Y). there is a partial influence between Trust (X2) on the Purchase Decision (Y) of the Lazada marketplace . There is a simultaneous influence between sales promotion (X1) and trust (X2) on purchasing decisions (Y) Lazada marketplace.

Ratio F test for testing simultaneous hypotheses in models with blocked compound symmetric covariance structure

This article deals with testing simultaneous hypotheses about the mean structure and the covariance structure in models with blocked compound symmetric (BCS) covariance structure. Considered models are used for double multivariate data, which means that m-variate vector of observation is measured repeatedly over u levels of some factor on each of n individual. Additionally, the assumption of multivariate normality for this type of data is made. We use framework of ratio of positive and negative parts of best unbiased estimators to obtain simultaneous F test. The test statistic is constructed as a ratio of test statistics for testing single hypotheses about the mean vector and the covariance matrix. In simulation study power of obtained test is compared with powers of three other F tests—two for testing single hypotheses and one for testing simultaneous hypotheses, whose test statistic is convex combination of test statistics of these two single F tests. The problem of simultaneous testing of the mean vector and covariance matrix was also consider in paper (Hyodo and Nishiyama, Commun Stat Theory Methods, https://doi.org/10.1080/03610926.2019.1639751, 2019).

PENGARUH GREEN MARKETING DAN BRAND IMAGE TERHADAP KEPUTUSAN PEMBELIAN PRODUK THE BODY SHOP INDONESIA (Studi Kasus Pada Followers Account Twitter @TheBodyShopIndo)

This research aims to determine the influence of Green Marketing and Brand Image to purchase decisions of The Body Shop Indonesia product empirically, both partially and simultaneously. The population of this research is a Twitter account follower @The Body Shop Indo who has made a product purchase at least twice in the last year. The study used samples of 100 respondents in which a questionnaire was implemented through direct message facilities on Twitter social media. Sampling uses non-probability sampling method with purposive sampling method. Methods of data analysis using multiple linear regression tests, with partial and simultaneous hypotheses test processed using SPSS program version 21.0. The results of this research show that the two independent variables, namely green marketing and brand image, are positive and significant both partially and simultaneously on dependent variables of the purchase decision. In addition, in this study green marketing and brand Image explained the purchasing decision of 52.9%, the rest is 47,1% influenced by other factors. Therefore, further researchers are advised to add another variable that affects purchasing decision. Keywords: Green Marketing, Brand Image, Purchasing Decision, The Body Shop

Simultaneous hypotheses testing in models with blocked compound symmetric covariance structure

In this article, authors consider simultaneous testing hypotheses about structure of mean vector and covariance matrix in models with some special covariance structure, so-called blocked compound symmetric (BCS) covariance structure, for variate observations over u levels of some factor on each of n individual under the assumption of multivariate normality. Authors, using framework of ratio of positive and negative parts of best unbiased estimators, obtain test statistic for simultaneous test and prove that under null hypothesis the statistic has exact F distribution. Simulation study is conducted to show strong and weak sides of considered test which is compared with two other F tests for testing single hypotheses about mean and covariance matrix.

The Effect of Discipline and Work Environment on Employee Performance in Ciputat Sector Police

Human Resources (HR) is very important to be able to carry out the role of tasks, operationalize the available technology and provide innovative and creative thinking. The purpose of this study was to determine how the Effect of Discipline and Work Environment on Employee Performance in Ciputat Sector Police, where the independent variables studied were Discipline (X1) and Work Environment (X2), while the dependent variable was Employee Performance (Y). This method uses a quantitative approach, with the nature of descriptive associative research. The statistical tool used in the form of multiple linear regression, and carried out through the SPSS program 20 populations taken were Ciputat Sector Police officers as many as 108 people and the sample technique used was using the Slovin formula so that the number of respondents sampled was 52 people. In testing the hypothesis the author uses the t test for partial hypotheses and the f test for simultaneous hypotheses. Based on partial hypothesis testing using the f test and t test where the test results show that the fcount is 201.736> and f table is 3.190 which means the independent variable (X) has an influence on employee performance while the results of the t test results in disciplinary variables produce t arithmetic 4,613> and t table 2,009 which means tcount> ttable and work environment variables produce t arithmetic of 6.353> and t table of 2.009 which means tcount> with a contribution value of 89.2% which means that the contribution of the Disciplinary variable ( X1) and Work Environment (X2) affect the variable Y (Employee Performance) that is equal to 89.2% while the remaining 10.8% variable Y (Employee Performance) is influenced by other factors not examined by the author.

Shopping Analysis in on Line Shop with Young People

On Line Shop Research with variable ease of shopping, product quality shopping. This study among young people aged18-28 years, residing in Jakarta, Tangerang and Tangerang Selatan, Bogor, Bekasi, Indonesia. A multivariate questionnaire withclosed questions. Likert Scale 1 - 5. Number of questionnaires 128 respondents with 69 male respondents and 59 femalerespondents. The quantitative analysis method uses a multiple linear regression analyz of IBM SPSS version 23 for analysis ofdetermination (R Square), tested partially (t test) and simultaneous (test F) hypotheses with alpha 5 percent (0.05). Results ofdetermination analysis (R Square) 0.172 for variable ease of shopping, product quality and shopping on the store on line. Resultsof hypothesis partially test (t test) 2,915 for ease of shopping and 3,672 for product quality. Simultaneous test results (test F)obtained 0.000 results below the maximum value of alpha 5 percent (0.05).

Polypharmacological in Silico Bioactivity Profiling and Experimental Validation Uncovers Sedative-Hypnotic Effects of Approved and Experimental Drugs in Rat.

In this work, we describe the computational ("in silico") mode-of-action analysis of CNS-active drugs, which is taking both multiple simultaneous hypotheses as well as sets of protein targets for each mode-of-action into account, and which was followed by successful prospective in vitro and in vivo validation. Using sleep-related phenotypic readouts describing both efficacy and side effects for 491 compounds tested in rat, we defined an "optimal" (desirable) sleeping pattern. Compounds were subjected to in silico target prediction (which was experimentally confirmed for 21 out of 28 cases), followed by the utilization of decision trees for deriving polypharmacological bioactivity profiles. We demonstrated that predicted bioactivities improved classification performance compared to using only structural information. Moreover, DrugBank molecules were processed via the same pipeline, and compounds in many cases not annotated as sedative-hypnotic (alcaftadine, benzatropine, palonosetron, ecopipam, cyproheptadine, sertindole, and clopenthixol) were prospectively validated in vivo. Alcaftadine, ecopipam cyproheptadine, and clopenthixol were found to promote sleep as predicted, benzatropine showed only a small increase in NREM sleep, whereas sertindole promoted wakefulness. To our knowledge, the sedative-hypnotic effects of alcaftadine and ecopipam have not been previously discussed in the literature. The method described extends previous single-target, single-mode-of-action models and is applicable across disease areas.

DETERMINANTS OF ECONOMIC EXPOSURE: AN EMPIRICAL EVIDENCE FROM THE MISCELLANEOUS COMPANIES IN INDONESIA

This research empirically measures the economic exposure of 11 selected miscellaneous companies in Indonesia. It also attempts to empirically explore the influence of firm size, export, liquidity, and leverage on the economic exposure of those companies. Annual data from 2007 to 2010, which was collected from thewww.idx.co.id andwww.bi.go.id were used and analyzed by the multiple linear regression to measure the economic exposure and examine the influences of the firm size, export, liquidity, and leverage on the economic exposure. Both partial (t-test) and simultaneous (F-test) hypotheses were constructed and tested using the software of SPSS for Windows. The research documented that, with the exception of the liquidity, which has a negative and significant effect partially on the economic exposure, all other variables, i.e., the firm size, export, and leverage were found to have insignificant effects. Meanwhile, based on the F-test, the research found that the firm size, export, liquidity, and leverage affected simultaneously and significantly the economic exposure of the companies. These findings imply that in order to manage their economic exposure, the companies should control these variables, especially the liquidity.

Impact of Psychological Contract Breach and Psychological Contract Fulfillment on Employees’ Intention to Quit In Telecom Sector of Pakistan

Purpose The paper is proposed in order to examine the relationship between psychological contract breach and fulfillment on employees' intention to quit. It seeks to present two simultaneous hypotheses, based on theoretical relations effects of all the three variables (psychological contract breach, fulfillment and intention to quit). Design - The data was collected from a sample of 300 employees in telecom sector of Rawalpindi/Islamabad, Pakistan. Correlation/Regression analysis was used to explore the relationships between psychological contract breach, fulfillment and employees' intention to quit. Findings - A positive relationship was found between psychological contract breach and intention to quit behavior of employees and a negative relationship between psychological contract fulfillment and intention to leave. Research limitations/implications -Future research can however focus on the conditions under which psychological contract both breach and fulfillment will have an impact on employee's intention to leave the organization.

The Improved Particle Filtering Algorithms for Tracking the Signals

The problem of tracking curves in dense visual clutter is challenging. Kalman filtering is inadequate because it is based on Gaussian densities which, being unimodal, cannot represent simultaneous alternative hypotheses. The PF(Particle Filtering) algorithm uses “sequential importance sampling”, previously applied to the posterior of static signals, in which the probability distribution of possible interpretations is represented by a randomly generated set. PF uses learned “sequential Monte Carlo” models, together with practical observations, to propagate and update the random set over time. The result is highly robust tracking of agile motion. Not withstanding the use of stochastic methods, the algorithm runs in near Real-Time.

A statistical methodology for analyzing co-occurrence data from a large sample

Determining important associations among items in a large database is challenging due to multiple simultaneous hypotheses and the ability to select weak associations that are statistically but not clinically significant. The simple application of the χ 2 test among all possible pairs of items results in mostly inappropriate associations surpassing the traditional ( α = .05, χ 2 = 3.94) threshold. One can choose a stricter threshold to find stronger associations, but the choice may be arbitrary. We combined the volume test of Diaconis and Efron with a p-value plot to select a more rigorous and less arbitrary threshold. The volume test adjusts the p-value of the χ 2-statistic. A plot of adjusted p-values (1− p versus N p ), where N p is the number of test statistics with a p-value greater than p, should be linear if there are no true associations. The point where the plot deviates from a line can be used as a threshold. We used linear regression to select the threshold in a reproducible fashion. In one experiment, we found that the method selected a threshold similar to that previously obtained by manually reviewing associations.

A Bootstrap Test for Circular Data

ABSTRACT This article presents a bootstrap test for simultaneous hypotheses on the mean direction and the dispersion of a sample of i.i.d. circular observations with unimodal distribution. This test is a nonparametric extension of the multivariate saddlepoint test for wrapped symmetric α-stable models proposed by Gatto (2000). Because the test statistic has an asymptotic chi-squared distribution with second-order accuracy, the typical sampling stage of most bootstrap procedures is not required. A simulation study illustrates the numerical accuracy and the effectiveness of this new test. In this simulation, samples are generated from circular distributions within the wrapped symmetric α-stable class.

Reproductive health problems: genetics vs. environment

Reproductive health problems: genetics vs. environment

Multivariate Saddlepoint test for the wrapped normal model

In this article we show the effectiveness and the accuracy of the test statistic based on the expnnent of the saddlepoint approximation for the density of M-estimators, proposed by Robinson, Ronchetti and Young (1999), for testing simultaneous hypotheses on the mean and on the variance of a wrapped normal distribution. We base this test statistic on the trigonometric method of moments estimator proposed by Gatto and Jammalamadaka (l999b), which admits the M-estimator representation necessary for this test. This test statistic has an approximate chi-squared distribution, asympiotically up to the second order, and the high accuracy of this approximation is shown by numerical simulations.

Testing simultaneous hypotheses in pharmaceutical trials: a bayesian approach

The purpose of this paper is to compare the Bayes factor and the likelihood ratio test in a pharmaceutical trial where the two treatments are a new drug and a control (a positive control or a placebo). The goal is to jointly answer the questions (1) is the new drug or the control toxic? (2) Is the new drug more effective and safer than the control? We consider a bivariate model where each treatment is characterized by a target effect (a continuous primary response y) and by a side effect (a continuous supplementary response ξ). Using a Bayesian approach, we account for the uncertainty resulting from prediction of the side effect, by making use of the physician's prior inputs about the target-toxicity relationship and the maximum tolerated target effects that are considered to be safe. Finally, we consider an example about a sleeplessness drug, and we show that the Bayes factor provides a more flexible and informative tool than the likelihood ratio test in simultaneous testing. Advantages are greater when the number of experimental subjects is small.

A nested urban recreation site choice model

Abstract Nested and simultaneous site choice hypotheses are tested and compared by multinomial logit analysis of travel to urban forest recreation sites in the Chicago metropolitan area. The nested model fits the data better, demonstrates violation of the independence from irrelevant alternatives (IIA) assumption in the simultaneous model, and offers a somewhat different explanation of site choice behavior.

Personality, sexual behavior, and drug use revealed through latent variable methods

The interrelations between personality, sexual behavior, and drug use among adolescents and young adults are studied using recently developed causal modeling methods. Formally known as structural equation models, these methods require the researcher to specify a series of simultaneous hypotheses about the effects of certain latent or unmeasured constructs on other constructs, as well as how observed variables serve as indicators of the latent constructs. Statistical tests of the adequacy of these hypotheses are then made. This paper reviews several studies and reports on a new study designed to answer the following questions: (1) To what extent are masturbatory and coital responsiveness phenomenologically interchangeable aspects of sexuality among young women? (2) Does social assertiveness by women improve their sexual responsiveness? (3) Is adolescent dating and sexual involvement related to their use of drugs and alcohol? The last question is addressed using a new distribution-free statistical estimator.

Robust analysis of variance based upon a likelihood ratio criterion

SUMMARY Robust tests of general linear hypotheses in linear models are developed. These are likeli- hood ratio type tests in the same sense that M-estimates are maximum likelihood type estimates. Construction of the tests suggests a decomposition of the data into terms analogous to classical sums of squares, providing a robust analysis of variance. Asymptotic efficiency and robustness properties of the tests are the same as those of the M-estimates upon which they are based. Parameter estimation is usually only a first step in the analysis of data arising fromn a linear model. A classical least squares analysis often focuses upon the analysis of variance, which tests simultaneous hypotheses on large subsets of the parameters. Since the terms in a classical analysis of variance are quadratic forms in least squares estimates, one would expect that the sensitivity of the estimates to departures from normality should be inherited by the tests. In fact, for moderate to heavy tailed error distributions or in the presence of outliers, it appears that the classical F test does lose power. Calculations of relative efficiency for proce- dures proposed in this paper substantiate on theoretical grounds the possible inefficiency and lack of power of classical F tests. In this paper, Huber's M-estimates are adapted to hypothesis tests which can be termed likelihood ratio type tests. These procedures naturally generalize and bear a striking re- semblance to classical F tests. Robustness and efficiency properties of M-estimates apply directly to the proposed tests. Hence the case to be made for using likelihood ratio type tests rather than classical F tests is the same as that for using M-estimates in favour of least squares estimates: possible poor performance of the classical methods may be overcome with methods which perform well both when classical assumptions are met and when they are not. The proposed methods are natural, intuitive and as easily computed as M-estimates.