The Treatment Of Schizophrenia Varies - 1499 Words

The treatment of schizophrenia varies. Many patients are treated with drug. Current treatment modalities are somatic and psychotherapeutic which were performed in many different ways that associates with drug treatment. The somatic treatments for schizophrenia are all based on drug therapy and pharmacology (de Meduna). Of course, there have been previous approaches of treatment. Psychosurgery, which had been rejected, includes electro convulsive therapies, insulin coma, and various treatment that involved immersion in hot or cold baths. The pharmacological therapies currently applied all have scientific proof of their effectiveness, although the results of these studies have also provided that when drugs are stopped, relapse may occur†¦show more content†¦However, patients responds in different ways. The patients may have to try more than one medication to find the right dose. Neuroleptics drugs have different effects on various symptoms of schizophrenia. Positive symptoms are the ones which are affected by the drugs, hallucinations and some communication disorders are some examples. The negative symptoms are merely affected because it is believed that most negative symptoms are somewhat associated with positive symptoms (Kane). Social deficits are caused by patient s experience of positive symptoms. For example, patients experience intense anxiety from their hallucination which makes it difficult for them to have normal conversations with other people. So whenever, hallucination goes away so does the anxiety problem. Finding the right treatment takes time. Treatment with neuroleptic medication may instantly work for the patients. Studies suggested that within few days of application of the drug treatment, the symptoms occurrence reduce and positive symptoms which usually occurs for over 7 weeks and in the first week of treatment (Rosenheck). Drug treatment is by far the most effective treatment of schizophrenia. This treatment had reduced many symp toms of the disease (Grohol). The future development will also be prevented. Future drug treatment of schizophrenia will follow a more rational and sensible course, one based on better of how drug will be acting based on how the brain functions. Direct inquiries

The Decision Between Quantitative And Qualitative Data

One of the most important parts of establishing a research design involves the decision between quantitative and qualitative data. Each has its own strength and weaknesses that any successful research design must account for. Perhaps one of the easiest distinctions between the two rests in the sample size. While quantitative data normally involves a large n, or sample size, qualitative data involves a much smaller sample size in comparison. This smaller sample size allows qualitative researchers to focus more on each case, increasing the internal validity of the research, but limiting its external validity. Quantitative based research designs reverse this. The large sample size of quantitative data often makes it difficult for researches to establish causation among the independent and dependent variable(s). The external validly of such designs usually offsets this issue to some extent. Due to their large nature, and use of numerical data, quantitative research is much more replicabl e when compared to their qualitative counterparts. Unfortunately, the struggle between internal and external validity is a fundamental part of research. Even efforts to combine the two methods to form a ‘mixed methods research design’ ultimately fail to nullify the issue completely. Keeping this in mind, a quantitative analysis is the most logical given the specific research question and the data available. This chapter seeks to prove that there is a statistically significant difference inShow MoreRelatedResearch Methods Of Quantitative Research1087 Words   |  5 Pages Week 2 Assignment Adam Morrison PSY 326 Research Methods Jessica Lee Qualitative researchers are focused on interpreting and making sense out of what they observe rather than trying to simplify and quantify these observations by collecting and observing people, places and things in their natural setting. In doing this, researchers are able to investigate hypothesis with more freedom and rigidity while accepting the fact that they relinquish their ability to control direct and indirectRead MoreEssay on Business Research for Decision Making1696 Words   |  7 PagesBusiness Research for Decision Making The work of decision making involves choosing between issues that require attention, setting goals, designing suitable courses of action and choosing among several alternatives through the evaluation of each one of the alternatives. Of great importance in decision making is the choosing between the several alternatives. The effectiveness of this work of decision making is of great importance for the well being of every business activity and determines the successRead MoreQuantitative And Qualitative Research Design1695 Words   |  7 Pagesphenomena they are interested in studying. Among the most widely used methodologies are quantitative, qualitative, and mixed-method (Cozby Bates, 2012, Garza Landrum, 2015; Leedy Ormrod, 2013; Creswell, 2013; Gergen, 2015). Qualitative and quantitative research designs, for example, are types of research approaches that provide clear directions on how to carry out a research plan (Creswell, 2013). The quantitative research design is profoundly deep-rooted in the discipline of psychology where itRead MoreMarketing Research Tools Essay1198 Words   |  5 Pagesthe business. Primary data is collected with specific purpose of creating a marketing strategy for the business conducting the research. Research also can be broken down even further into quantitative and qualitative research methods. Both methods are highly effective and provide accurate results. However, it is important to gather the information most pertinent to the purpose of the research. Quantitative research focuses on the quantity of the research and qualitative research focuses on theRead More Marketing Research Tools Essay example1410 Words   |  6 Pagescompanies in the decision-making process and their marketing direction. Data from marketing research is important because it provides companies with ways to identify opportunities, identify market potential, minimize chances of loss, devise effective marketing strategies, gauge customer satisfaction, and serve as an evaluation tool. A wide-range of marketing research tools is available to market researchers and organizational decision makers. The following focuses specifically on data collection methodsRead MoreQuantitative, Qualitative, And Mixed Methods1467 Words   |  6 Pagesdesigns for quantitative, qualitative, and mixed methods. The qualitative methods do not usually involve statistical analysis. Then again, the quantitative methods essentially include the statistical analysis. Every one of these perspectives might be inspected while defining the hypothetical design for the research. Understand that research questions and research hypotheses are not the same thing. Research questions must foreshadow the data analyses. The overriding purpose of quantitative researchRead MoreMarketing Research Assignment1542 Words   |  7 Pagesa good research to realize the customers need is very important. Qualitative research and quantitative research are the main method to collect information and data from customers for making firm’s decision. However, there is a different between qualitative and quantitative which used in different part of projects. And they both have advantages and disadvantages in the process and the conclusion which may lead to incorrect decisions. Indeed, to distinguish two research methods and when to use orRead MoreWeek 1 RSCH 8300860 Words   |  4 PagesInitial post Comparing Qualitative and Quantitative Approaches Researchers often times are faced with the decision of choosing a methodology of research; either Quantitative or Qualitative that they think best fits their study and objectives. This choice is guarded by the topic of study, the advantages and disadvantages, and the strengths and weaknesses of using either one or the other type of the methodologies. Researchers are sometimes using Quantitative and Qualitative research methodologies interchangeablyRead MoreThe Social Construction Of Experience1437 Words   |  6 PagesIn particular, qualitative researchers tend to focus more on the social-constructed reality and the contextual influence, interaction and constraints between the researcher(s) and the participants. They are interested in finding answers to questions that focus on the â€Å"social construction of experience and how meaning is created† (Cooper White, 2012, p. 15). However, quantitative researchers â€Å"emphasize measurement and analysis, and focus on product rather than process† (Cooper White, 2012, p.Read MoreQualitative And Quantitative Research Methods1285 Words   |  6 Pages Qualitative and Quantitative Research Ravi Teja Mora Dr. Jimi Peters Research Methods Stratford University â€Æ' Qualitative and Quantitative Research Introduction There has been a widespread of debate in recent years regarding the quantitative and qualitative research methods, wether one or the other has to be emerged as superior. Although there have been so many theories and conclusions, this paper intends to discuss on the similarities and differences between the qualitative and quantitative research

Critical study of the parametric model development process Free Essays

string(92) " but the configuration management and long-term maintenance issues still must be addressed\." Abstract: Complex parametric models may consist of many interrelated cost estimating relationships (CERs), as well as other equations, ground rules, assumptions, and variables that describe and define the situation being studied. Models generate estimates based upon certain input parameters, or cost drivers. Parametric models can generally be classified as commercial or company-developed. We will write a custom essay sample on Critical study of the parametric model development process or any similar topic only for you Order Now This review provides practical information about developing, deploying, and maintaining company-developed parametric models. Company-developed models – also referred to as company-owned, in-house, or proprietary models – differ from cost estimating relationships (CERs) because of their higher level of complexity, and the range of costs they estimate. Commercial parametric estimating models, available in the public domain, use generic algorithms and estimating methods which are based on a database that contains a broad spectrum of industry-wide data. Unlike commercial models, company-developed models are designed for the specific estimating needs of an organization or to describe a particular product. A proprietary model offers an alternative to trying to use a commercial model to meet an organization’s unique estimating requirements. JEL classification: C50, C51 Key words: equation, parameter, parametric model, commercial model, proprietary model 1. Introduction A parametric cost model can be viewed as the collection of databases, cost estimating relationships (CERs) [1], cost factors and algorithms, which together are used to estimate the costs of a system and its components. A parametric cost model uses known values to estimate unknown ones. Industry use parametric models to support conceptual estimating, design-to-cost analyses, life-cycle cost estimates, risk analyses, budget planning and analyses. Parametric models can also be used as the basis of a cost estimate in preparation of firm business proposals, or in the independent assessment of cost estimates prepared using a traditional estimating approach. Models generate estimates based upon certain input parameters, or cost drivers. Parameters â€Å"drive the cost† of the end product or service being estimated. Some examples are weight, size, efficiency, quantity, and time. Some models can develop estimates with only a limited set of descriptive program inputs; others, however, require the user to provide many detailed input values before the model can compute a total cost estimate. A model can utilize a mix of estimating methods, and it may allow as inputs estimates from other pricing models (or information systems) or quotes from external sources, such as subcontracts. Several companies implemented commercial parametric estimating hardware models, which can rapidly compute development and design costs, manufacturing costs of prototypes, and production unit/manufacturing support costs. Commercial parametric estimating models use generic algorithms and estimating methods which are based on a database that contains a broad spectrum of industry-wide data. Because this data encompasses many different products, a company working with a commercial parametric model must calibrate it before using it as a base of estimate for proposals submitted to the higher-tier contractors. Calibration tailors the commercial model so it reflects the products, estimating environment, and business culture of that particular company. A proprietary model offers an alternative to trying to use a commercial model to meet an organization’s unique estimating requirements. Proprietary models are developed for an organization’s own product and cost estimating needs and are, in effect, self-calibrated. Proprietary models can be implemented for a variety of estimating purposes, and have a wide range of complexity, completeness, and application. 2. The Proprietary Model Development Process The major activities involved in developing a proprietary model are: Step 1: Identifying the Parametric Model Opportunity One of the most critical steps in the proprietary model development process is the identification of a good opportunity for implementing a parametric model. This involves two points. First, it is important to investigate the feasibility of developing the model, which entails an evaluation of both its technical feasibility and cost effectiveness. Technical feasibility refers to the ability of the model to meet the estimating needs of the organization, and examines whether the organization has the resources to develop the model within a reasonable timeframe. This includes performing a cost-benefit analysis to decide whether a proprietary model would be cost-effective to implement and maintain. All potential benefits should be considered in the cost-benefit analysis; for example, contractors have achieved significant savings in proposal preparation, evaluation, and negotiation through the implementation of proprietary parametric estimating models. Other contractors have achieved additio nal benefits through multiple applications of the same model, such as for design studies, target costing, and contract risk management as well as basic estimating. The second critical point involves gaining the support of internal upper-level (including program) management and key customer management. If the model then meets the acceptance criteria provided by these groups, they agree to support its proper application in subsequent proposals. Little good comes from implementing a proprietary model if there is no internal management buy-in, or no support from the key customers on the estimating technique. Also, the firm’s management will want to understand the results of the feasibility study so it can properly assess the financial investment required to support model development and on-going maintenance activities, such as training, model enhancements, and software corrections. On receiving approval to begin development from internal and external management, the contractor establishes an implementation team to guide the creation of a valid proprietary model. This team should include representatives from the company and key customers. Step 2: Information Systems Needs When implementing a proprietary model, the organization should commit and obtain the necessary resources for information systems development and support activities. Information systems support is required for a variety of functions: – defining the formal system requirements needed to support the cost estimating model (e.g., hardware, software, interfaces with other systems); – testing the model to ensure it adequately satisfies all end-user requirements; – maintaining the integrity of the model throughout its life span by establishing procedures to manage and control all changes (i.e., configuration management); – providing software support services once the model is deployed to keep it operational (e.g., corrections, revisions, miscellaneous enhancements). When simpler models are implemented (e.g., spreadsheet models), the degree of support is smaller, but the configuration management and long-term maintenance issues still must be addressed. You read "Critical study of the parametric model development process" in category "Essay examples" Step 3: Data Collection and Analysis Historical costs should be used, with the development team ensuring that they are relevant to the firm’s current operating procedures. In an effort to include as much relevant cost data as possible, analysts normalize it as it is incorporated into the database [2]. They adjust data so it is as homogeneous as possible (e.g., similar in content, time value of money, quantity), and does not contain anomalies. Programmatic, noncost data may also require normalization. The analyst must assess the condition of each program’s data and make appropriate adjustments as required. When developing a model, the team identifies the main characteristics, called the primary cost drivers, that are responsible for, and have the greatest impact on, the product or services cost to be estimated. Step 4: Model Development The development of a proprietary model incorporates many anticipated uses and goals – such as estimating/users’ requirements, availability of credible data, life-cycle costs, systems engineering costs, forward pricing rates – and it must integrate these into the parametric estimating approach. The modeling process, in particular, focuses on these tasks: – specifying the estimating methods for accomplishing the estimating goals; -identifying the job functions and other elements of cost that will be estimated; – defining data input structures; Proprietary models may contain a number of different estimating techniques. Step 5: Calibration and Validation Parametric models are calibrated and validated before they are used to develop estimates for proposals. Since proprietary models are based on an organization’s historical data, they are considered to be self-calibrated. Validation is the process, or act, of demonstrating the proprietary model’s ability to function as a credible estimating tool [3]. Validation ensures: – estimating system policies and procedures are established and enforced; – key personnel have proper experience and are adequately trained; – proper information system controls are established to monitor system development and maintenance activities in order to ensure the model’s continued integrity; – the model is a good predictor of costs. Models should be validated and periodically updated to ensure they are based on current, accurate, and complete data, and that they remain good cost predictors. The purpose of validation is the demonstration of a model’s ability to reliably predict costs. This can be done in a number of ways. For example, if a company has sufficient historical data, data points can be withheld from the model building process and then used as test points to assess the model’s estimating accuracy. Unfortunately, data sets available are often extremely small, and withholding a few points from the model’s development may affect the precision of its parameters. This trade-off between accuracy and testability is an issue model developers always consider. When sufficient historical data are not available for testing, accuracy assessments can be performed using other techniques. Another testing methodology compares a commercial program’s final cost to the proprietary model’s estimate of it. However, it may be months, or years, before this approach can be applied to a given program. The model team may use this method when a program is near completion, or is at a point where a meaningful earned value performance index for it can be determined. Step 6: Estimating System Policies and Procedures After validation, the company must modify its estimating system policies and procedures to explain the appropriate use and application of the model for reviewers and company users. In particular, the model’s developers need to document its proper use as a valid bidding tool. Companies should also explain the model’s design, development, and use. For example, the contractor, as part of its support for the follow-on production model and estimating tool, developed a detailed manual containing information about the mechanics of the model, its estimating methodologies, and the timing of updates. The company also amended its Estimating System Manual to include a section on the model, and to refer the reader to the model’s own manual. Step 7: Internal Approval Process Model developers need to assure company representatives that the model relies on the firm’s historical data and, therefore, captures how the company executed similar projects in the past. Any departmental budget allocations produced by the model should reflect the average budgetary split the firm has historically experienced. Developers should also consider the fact that a model, if approved, might change the way the company anticipates executing an existing (or planned) program (e.g., the project director may need to shift work and modify the budget). This obviously affects the circumstances under which other company personnel would approve the model. A best practice from contractor experience involves the integration of the company representatives into the model implementation team. As an example, when implementing the follow-on production model, the model designers, from the beginning, solicited the participation of key internal representatives. During the development of each module, the team incorporated the inputs of the functional department primarily responsible for executing that portion of the project which the module was designed to estimate. Although the Finance Department led the model building effort, it continuously reviewed its progress with representatives from the Engineering and Manufacturing Departments. These representatives were responsible for coordinating and obtaining any necessary information from their organization, and keeping management informed. Step 8: External Approval Process Although a company may internally approve a model, the customer must also be shown that the estimating approach is valid. The involving of customers in up-front decision facilitates their acceptance of parametric techniques. In seeking acceptance of a proprietary model, the company formed a Continuous Improvement Process (CIP) team [4]. The team’s composition included company representatives from various departments. All team members participated in establishing selection criteria for the model’s database. Based on the selection criteria, the contractor personnel collected actual cost data from many contracts. When using the model for the first time with a buying organization, the CIP team invites the buying organization to the company for a joint review and explanation of the model. Immediately after obtaining funding to develop the model, the developing company discussed it with other contractors, additional government organizations, to ensure widespread support in data collection and model validation. Including customers on the development team does not guarantee a model’s acceptance, of course. It does ensure that the customer has a voice in the model’s design and usage, but the model’s ability to reasonably predict costs is the ultimate basis for acceptance. No person, internal or external to the company, can prove this before final development and testing. Step 9: Model Maintenance Through the development process, the team develops a sense of how often the model needs updating. Maintenance activities include not only the incorporation of new data into the model, but also an evaluation of the mathematical relationships between the technical parameters and the costs the model estimates. Periodic evaluation of the model is required to ensure the estimates are relevant and the contractor is using the most current, accurate, and complete data. New data is contributed as programs mature and, occasionally, from non-company sources. In some situations, the cost modelers develop new CERs, based on a subset of the original database, in order to better match a new estimating requirement. The process of maintaining a model involves keeping an audit trail of the CERs developed, the data points used, and their statistical effectiveness. 3. Conclusions Company-developed parametric models – also known as proprietary models offers an alternative to use a commercial model regarding organization’s own product and cost estimating needs. No company or individual can develop a valid model without the participation of a number of key people which include the customers, all interested company personnel, and government representatives. Some concepts should be considered by all implementation teams as follows: – establish a process flow and target development dates to ensure all team members provide their inputs to the model’s design; – consider the costs and benefits of model development; – evaluate commercial models as an alternative to proprietary development; – remember that the goal is to establish a more efficient and reliable estimating system, not just create a model. References Stuparu D., Vasile T., Stanciu M. The Cost Estimating Relationships (CER’s) – modern method for predicting cost, Revista Academiei Fortelor Terestre, nr. 1/2010. Vasile T., Stuparu D., Daniasa C.I. Collection and Normalization of Parametric Data, Analele Universitatii din Oradea, Tom XVIII, vol. II, 2009, pp. 703-708. Stewart R.D., Wyskida R.M., Johannes J.D. Cost Estimator’s Reference Manual, 2nd Edition, New York, Wiley, 1995, pp. 57-67. * * *http://www.ceh.nasa.gov/webhelpfiles/Cost_Estimating_Handbook_NASA_2004.htm How to cite Critical study of the parametric model development process, Essay examples