Meta Analysis

Meta-Analysis of Correlations
By. Dr. Andy Field

Meta analysis is a statistical technique by which information from independent studies is assimilated. Traditionally, social science literatures were assimilated through discursive reviews. However, such reviews are subjective and prone to reviewer-biases such as the selective inclusion studies, selective weighting of certain studies, and misrepresentation of findings (see Wolf, 1986). The inability of the human mind to provide accurate, unbiased, reliable and valid summaries of research created the need to develop more objective methods. Meta-analysis arguably provides the first step to such objectivity (see Schmidt, 1992), although it too relies on subjective judgments regarding study inclusion (and so is still problematic because of biased selections of studies, and the omission of unpublished data-the file drawer problem). since the seminal contributions of glass (1976), Hedges and Olkin (1985), Rosenthal and Rubin (1978) and Hunter, Schmidt and Jackson (1982) there has been a meteoric increase in the use of meta analysis. Field (2001) reports that over 2200 published articles using or discussing meta-analysis were published between 1981 and 2000. of these, over 1400 have been published since 1995 and over 400 in the past year. Clearly, the use of meta-analysis is still accelerating.

Basic Principles

To summarise, an effect-size refers to the magnitude of effect observed in a study, be that the size of a relationship between variables or the degree of difference between group means. There are many different metrics that can be used to measure effect size: the Person product moment correlation coefficient, r; the effect-size index, d; as well as odds ratios, risk rates, and risk differences. of these the correlation coefficient is used most often (Law, Schmidt, & Hunter, 1994) and so is the focus of this study. Although various theorists have proposed variations on these metrics (for example, Galss's delta, cohen's d, and Hedges's g are all estimates of Thou), conceptually each metric represents the same thing: a standardized from of the size of the observed effect. Whether correlation coefficients or measures of differences are calculated is irrelevant because either metric can be converted into the other, and statistical analysis procedures for different metrics differ only in how the standard errors and bias correlations are calculated (Hedges, 1992).

In meta-analysis, the basic principle is to calculate effect sizes for individual studies, convert them to a common metric, and then combine them to obtain an average effect size. Studies in a meta-analysis are typically weighted by the accuracy of the effect size they provide (i.e. the sampling precision), which is achieved by using the sample size (or a function of it) as a weight. Once the mean effect size has been calculated it can be expressed in terms of standard normal deviations ( a Z score) by dividing by the standard error of the mean. A significance value (i.e. the probability, p, of obtaining a Z score of such magnitude by chance) can then be computed. Alternatively, the significance of the evarage effect size can be inferred from the boundaries of a confidence interval constructed around the mean effect size.

Johnson, Mullen and Salas (1995) point out that meta-analysis is typically used to address three general issues: central tendency, variability and prediction. Central tendency relates to the need to find the expected maginitude of effect across many studies (from which the population effect size can be inferred). this need is met by using some variation on the average effect size, the sinificance of the this average or the confidence interval around the average. The issue of variability pertains to difference between effect sizes acrosss studies and is generally adressed using tests of the homogenity of effect sizes. The question of prediction relates to the need to explain the variability in effect size across studies in terms of moderator variables. This issue is usually addressed by comparing study outcomes as a function of differences in characteristics that vary over all studies. As an example, differences in effect sizes could be moderated by the fact that some studies were carried out in the USA whereas others were conducted in the UK.

My GIS Project

Peta Penggunaan Lahan



Note: This is just an example (in jpg format)

GIS

Introduction to ArcGIS

By Kardi Teknomo, PhD.

GIS is abbreviation of Geographic Information system. Aside from buzzwords and much hype about it, GIS in a very simple term is just a combination of Maps and database. In other words, GIS is a spatial database .

Map is a very useful geographical tool to show the location of places. You may have learned about the world map with many countries in it.

You may have recognized city map with district boundary and road and railway as shown below.

For those of you who do not even know what a database is, you can imagine a database as relational tables .

Database is more than a simple table because in it you can do some query (search back for some data) and make relationship between one table and the other tables.

GIS is a combination of Maps and Database. Depending on how we represent the map, every element in the map may have an association or connection with some database table. For example, selecting a country in the world map that has an association with a table will show all the attributes data related to that selection.

Maps in GIS can be separated into several layers. Each layer map can be viewed in combination with some other layers, or it can be seen as a separate layer. You may extract some information based on these layers. For instance, you may search for some location based on several criteria, or find some pattern over several years map, query features that near to some other feature, and so on. Later in this series of GIS tutorial, you may learn further query, analysis, and modeling and enhance decision support system using the power of GIS.

My choice of ArcGIS (I am using version 8, version 9 may be slightly different in menu) is simply because its availability and my own familiarity with this software. Even if you do not have ArcGIS, you may browse this tutorial to gain understanding on what you can do using GIS. I also provide a list of other GIS software both commercial and free version in the GIS Resources page.

ArcGIS is a product of ESRI. The latest version is available in three different editions under three different names:
-ArcView (simple, Standard edition)
-ArcEditor (functional, Professional edition)
-ArcInfo (advance; Enterprise edition)

Do not be confused with the name of the editions. The three editions above share the same architecture and have the same way on how to use. The differences are prices and more tools/functions.

If you open the menu in ArcGIS, you may see many icons. The first question is, perhaps, which one to use?
Regardless your editions, ArcGIS will contain at least three main softwares
ArcCatalog,
ArcMap, and
ArcToolbox

ArcCatalog is similar to Windows Explorer. With ArcCatalog you may preview your GIS data in term of geography (map) or table. If your data contain 3D scene, you can use ArcCatalog to preview the content. You can create file, folder and meta-data of your GIS data using this software. If your data is a map file, you can double click to open it in ArcMap, otherwise, you can do drag and drop of your GIS data into ArcMap.

ArcMap is the main software that you use for GIS. Using ArcMap you can create and edit your map, layers, and charts. You may perform some analysis and query on your GIS data using ArcMap.

ArcToolbox is a collection of Analysis Tools (e.g. extract, overlay, proximity, statistics, surface cut and fill, volume and contour), Conversion Tools (i.e. import to / export from different type of files) and Data and Management Tools (e.g. Join tables, define projections, etc.)

If you ArcGIS contain ArcScene, it is useful for showing your map in 3 dimension. ArcScene is similar to ArcMap with more functional in 3D scene analysis, but you cannot create map in ArcScene.

The rest of this tutorial will cover only ArcCatalog and ArcMap since it is the main software of ArcGIS.

Build an Executive Information System

Microsoft Office Excel 2007 Visual Basic for Applications Step by Step
by Reed Jacobson
Microsoft Press 2007 (384 pages)
ISBN:9780735624023

Experience learning made easy, and quickly teach yourself Microsoft Office Excel 2007 VBA--one step at a time! With help from this friendly book, you'll learn to automate spreadsheets, write functions and procedures, customize menus, toolbars, and more!
Table of Contents
Microsoft Office Excel 2007 Visual Basic for Applications Step by Step
Features and Conventions of This Book
Using the Book’s CD
Getting Help
Chapter 1 - Make a Macro Do Simple Tasks
Chapter 2 - Make a Macro Do Complex Tasks
Chapter 3 - Explore Workbooks and Worksheets
Chapter 4 - Explore Range Objects
Chapter 5 - Explore Data Objects
Chapter 6 - Explore Graphical Objects
Chapter 7 - Control Visual Basic
Chapter 8 - Extend Excel and Visual Basic
Chapter 9 - Launch Macros with Events
Chapter 10 - Use Dialog Box Controls on a Worksheet
Chapter 11 - Create a Custom Form
Appendix A - Complete Enterprise Information System
Index
List of Figures
List of Sidebars
CD Content

This is an interesting book he..he...Build your executive information system by visual basic in excel, Now.

Simulation and Monte Carlo: With applications in finance and MCMC

Simulation and Monte Carlo: With applications in finance and MCMC
By. LSC forum
Paperback: 348 pages
Data: March 23, 2007
Format: PDF

Description: Simulation and Monte Carlo is aimed at students studying for degrees in Mathematics, Statistics, Financial Mathematics, Operational Research, Computer Science, and allied subjects, who wish an up-to-date account of the theory and practice of Simulation. Its distinguishing features are in-depth accounts of the theory of Simulation, including the important topic of variance reduction techniques, together with illustrative applications in Financial Mathematics, Markov chain Monte Carlo, and Discrete Event Simulation.

Each chapter contains a good selection of exercises and solutions with an accompanying appendix comprising a Maple worksheet containing simulation procedures. The worksheets can also be downloaded from the web site supporting the book. This encourages readers to adopt a hands-on approach in the effective design of simulation experiments.

Arising from a course taught at Edinburgh University over several years, the book will also appeal to practitioners working in the finance industry, statistics and operations research.

Click Download

Information System Key Issues

A. Title: Key Issues in Information Systems Management:A Shift Toward Technology Infrastructure
By. James C. Brancheau, Brian D. Janz, James C. Wetherbe

1994 Key Issues Framework
1 Building a Responsive IT Infrastructure
2 Facilitating and Managing Business Process Redesign
3 Developing and Managing Distributed Systems
4 Developing and Implementing an Information Architecture
5 Planning and Managing Communication Networks
6 Improving the Effectiveness of Software Development
7 Making Effective Use of the Data Resource
8 Recruiting and Developing IS Human Resources
9 Aligning the IS Organization within the Enterprise
10 Improving IS Strategic Planning
11 Implementing and Managing Collaborative Support Systems
11 Measuring IS Effectiveness and Productivity
13 Increasing Understanding of IS Role and Contribution
14 Facilitating Organizational Learning
15 Managing the Existing Portfolio of Legacy Applications
16 Facilitating and Managing End-User Computing
17 Using Information Systems for Competitive Advantage
18 Planning and Integrating MultiVendor Open Systems
19 Developing and Managing Electronic Data Interchange
20 Outsourcing Selected Information Services
-- Implementing Decision and Executive Support Systems dropped --
-- Improving Information Security and Control dropped --
-- Developing and Implementing Object-Oriented Technology dropped --
-- Improving Disaster Recovery Capabilities dropped --
-- Developing and Implementing Multimedia Applications dropped --
-- Implementing and Integrating CASE Technology--dropped
Note: All data are from the final round of the Delphi survey (N = 83).

B. Title: Critical Issues of Information Systems Management in Hong Kong
By. Louis C.K. Ma

Critical Issues of IS Management (1999)
1. Improving the Effectiveness of Software Development
2. Building a Responsive IT Infrastructure
3. Increasing Understanding of IS Role and Contribution
4. Making Effective Use of the Data Resource
5. Developing & Implementing an Information Architecture
6. Aligning the IS Organization within the Enterprise
7. Improving IS Strategic Planning
8. Using Information System for Competitive Advantage
9. Facilitating and Managing End-User Computing
10. Managing the Existing Portfolio of Legacy Applications
11. Measuring IS Effectiveness and Productivity
12. Planning and Managing Communication Networks
13. Improving Information Security and Control
14. Facilitating and Managing Business Process Redesign
15. Recruiting and Developing IS Human Resources
16. Establishing Effective Disaster Recovery Capabilities
17. Facilitating Organization Learning
18. Implementing and Managing Collaborative Support System
19. Planning and Integrating Multi-Vendor Open System Technologies
20. Developing and Managing Distributed Systems
21. Facilitating/Managing Decision and Executive Support Systems
22. Developing and Managing Electronic Data Interchange (EDI)
23. Outsourcing Selected Information Services
24. Planning and Using CASE Technology

1. Improving the Effectiveness of Software Development
The application development backlog remains at unacceptably high levels. Traditional development methods and platforms are no longer satisfactory. New methods and platforms have not yet proven themselves. Sophisticated users are getting impatient. Improved effectiveness will be essential for next-generation applications.

2. Building a Responsive IT Infrastructure
Building a technology infrastructure that will support existing applications while remaining responsive to change is a key to long-term enterprise productivity. This task is frustrated by the continuing rapid changes in infrastructure technology and the increasing breadth and depth of applications, which need to be supported.

3. Increasing Understanding of IS Role and Contribution
IS is often viewed as an operational activity with little recognition for its strategic contribution to the organization. This can result in executive management viewing IS strictly as an overhead expense. Funding can be cut resulting in missed opportunities for using IT to solve important business problems.

4. Making Effective Use of the Data Resource
The organization’s data resource is growing in size, complexity, and value. Despite this, it remains largely unrecognized, inaccessible, and underutilized. IS must develop a climate within its department and throughout the organization which values the data resource as a corporate asset.

5.Developing & Implementing an Information Architecture
A corporate/global information architecture is needed to identify the major information categories used within an enterprise and their relationships to business processes. It is essential for guiding applications development and facilitating the integration and sharing of data.

6. Aligning the IS Organization within the Enterprise
The IS organization’s effectiveness in supporting the enterprise’s needs is dependent on its organizational location within the enterprise. Appropriate alignment may require a combination of centralized and decentralized structures. Too often IS is not located and structured appropriately.

7. Improving IS Strategic Planning
It has always been important to align long-rang IS plans with strategic business plans. Rapidly changing business environments, increased involvement of end users, and accelerated technological change underscore the need to continue improving strategic planning skills.

8. Using Information Systems for Competitive Advantage
In many businesses, long-term survival is dependent on using information systems to gain competitive advantage. Competitive advantage results from recognition of opportunities through creativity and innovation, followed by rapid implementation. These are historical weaknesses of the IS organization.

9. Facilitating and Managing End-User Computing
The proliferation of end-user computing through personal computers offers the promise of improved productivity but also the dangers of inadequate management control. Information systems management must balance control against the need for slack. Clarification of IS and end-user roles is a necessity.

10. Managing the Existing Portfolio of Legacy Applications
Most organizations have a large investment in their existing applications portfolio. Some “legacy” applications may need to be retired quickly. Others may need to be leveraged for many years before they are replaced. Integrating new technologies and migrating to new operating environments can be difficult. Too little is known about managing these problems.

11. Planning and Managing Communication Networks
Communication is the lifeblood of the organization. Using IS for competitive advantage depends heavily on access to appropriate internal and external communication networks. This task is complicated by rapid advances in underlying technology and major structural changes in the communications industry. (e.g. Internet, Intranet, Video Conferencing and Wireless Networks).

12. Measuring IS Effectiveness and Productivity
Understanding how IT use impacts the bottom-line is crucial for justifying new investment. In addition, measuring the IS organization’s performance is necessary for effective management. Measurement is becoming more important as companies attempt to reduce operating expenses to meet the competition.

13. Improving Information Security and Control
As organizations increase their dependence on information systems, there is a greater risk from destruction and alteration of data, disclosure to outside sources, and disruption of information services. Tight security controls and fault-tolerant information delivery are becoming a necessity.

14. Facilitating and Managing Business Process Redesign
To remain competitive, many organizations are radically changing the way they do business. IT plays an increasingly important role in this change process by enabling the innovative redesign of core business processes. Much has been learned about IT implementation in general which can help facilitate and manage BPR projects.

15. Recruiting and Developing IS Human Resources
Current and future shortages of qualified IS personnel threaten the organization’s ability to make effective use of information technology. More emphasis needs to be put on developing business skills such as object-oriented and multimedia applications.

16. Establishing Effective Disaster Recovery Capabilities
Downside risks are increasing daily from the potential loss of business due to a disaster. Effective recovery plans must be in place and tested regularly to ensure losses are minimized. As organizational applications grow and become more integrated, the greater the risk becomes.

17. Facilitating Organizational Learning
Organizations that prosper will need to make appropriate use of information technologies across their entire enterprise. Business practices and organizational structures will need to be modified in many cases. IS also must demonstrate its own ability to learn and use new technology.

18. Implementing and Managing Collaborative Support System
New software is needed to support the reengineered, flat, team-based organization of the future. Appropriate IT support can help teams share information and lead to faster decision making and improved team effectiveness. Such support will become even more important in a distributed ubiquitous computing environment.

19. Planning and Integrating Multi-Vendor Open System Technologies
Many companies are moving away from single-vendor proprietary operating environments to vendor-neutral environments based on industry and de facto standards. Due to large investments in legacy systems, carefully planned migration paths are critical. This task is complicated by a still-maturing technology and unstable standards.

20. Developing and Managing Distributed Systems
Client-server applications promise to offer a cost-effective alternative to centralized application. Unfortunately, they present many challenges including: maintaining consistent software versions; maintaining consistent data; controlling joint development projects with users; and administering large-scale distributed applications.

21. Facilitating/Managing Decision and Executive Support Systems
Increasing the ability to exploit situations for competitive advantage depends on enhancing the ability of management to “experiment” with decision possibilities. Many other issues also depend on this capability. Decision support tools have long been viewed as a method for introducing modelling tools to executives to improve their decision making. However, these efforts have met with mixed success.

22. Developing and Managing Electronic Data Interchange (EDI)
Electronic communication (via internet or proprietary EDI networks) with customers and suppliers may offer competitive advantage to a company or it may be a requirement for staying in business. IS executives must develop (or adapt to) standard transaction formats, keep current on technology developments, and learn to manage inter-organizational projects.

23. Outsourcing Selected Information Services
The internal information systems organization no longer has a monopoly. Outside contractors may be able to provide some services more effectively. What services should be outsourced? How should contractor relationships be managed? Fair and objective evaluation techniques are needed which assess both costs and benefits as well as potential risks from loss of control.

24. Planning and Using CASE Technology
Significant progress has been made automating business functions within organization; however, a vast productivity gain is possible if the automation process itself is automated. In principle, software systems can provide support for integrating the design efforts of project teams, standardizing representation methods, and generating code. While this technology is still being refined, providing support for systems development is extraordinarily complex and will require major changes within the IS function.

C. Title: Key issues in information systems management in China
By. Guoqing Chen, Ruipeng Wu and Xunhua Guo, 2007
(This article need permission by publisher)

Sources of Influence on Beliefs about IT Use: an Empirical Study of Knowedge Workers

An Article by William Lewis,Ritu Agarwal, V. Sambamurthy

This research examined the simultaneous of individual belief, institutional, and social context of influences on beliefs about usefulness and ease of use in the context of a contemporary technology targeted at autonomous knowledge workers.


Lewis et al. 2003 stated that research on individual beliefs as the main factor for the acceptance of an information system in an organization is acceptable. However, A research that focus only on the individual beliefs without understanding why the individual has the beliefs is no longer interesting. This is because we know that the beliefs is formed by a process from collecting, processing to synthesizing. Therefore, a factor that to be as antecedents of the beliefs need to be examined. Although there have been previous empricial studies that have examined the factors, but unfortunately the studies only focus upon a specific and limited set of antecedents.


The primary purpose of Lewis et al. 2003 research, therefore, was to present empirical evidence that institutional forces, social forces, and individual characteristics exhibit significant and differential impacts on two key individual beliefs about the use of information technologies such as beliefs related to usefulness and ease of use from Davis (1989) and Davis et al. 1989.


Lewis' et al.2003 findings suggest that beliefs about technology use can be influenced by top management commitment to new technology and the individual factors of personal innovativeness and self efficacy. Surprisingly, social influences from multiple sources exhibited no significant effects.


This research used field study research by inviting 1,121 academic faculty members that use internet technology in his/her activities to fulfill a paper form which was delivered via campus e-mail. Of These, 229 respondents have participated in this research, 181 of which were completed questionnaires and used for data analysis.


The data was analyzed using structural equation modeling by using partial least square. PLS, a latent structural equations modeling technique, was utilized to test the posited research hypotheses. PLS uses a component based approach to estimation that places minimal demands on sample size and residual distributions (Chin 1998). It also permits simultaneous analysis of both the measurement model and the
structural model.


The analysis data consist of descriptive statistics, factor analysis, inter-construct correlations, and t-test.


The implication of this research are:
1. Provide additional evidence regarding salient predictors of key beliefs in technology acceptance.


2. Help sift out and provide initial insights into the relative effects of these predictors on the target beliefs. Lewis et al. 2003 posited and confirmed that the effects of all factors are not invariant across beliefs. Institutional influences were most salient for instrumental outcomes, and individual factors, in contrast, were significant antecedents of both usefulness and ease of use. Finally, the
non-significance of social influences in this study is an interesting finding. It is possible that social influences manifest effects through beliefs not specifically examined in this work, such as image. Indeed, Venkatesh and Davis (2000) found a
significant relationship between subjective norm and image beliefs.



3. From a pragmatic perspective, it is evident that the institutional context for technology use is a critical predictor of individual behavior toward information technologies, via its effects on the mediating construct of beliefs. Our findings suggest that managers need to focus careful attention on exhibiting commitment to a new technology for contingent adoption decisions. Unless individuals perceive the power elite within the organization as strongly behind the use of a new technology
through the messages conveyed as well as overt and specific resource provisioning actions, they are unlikely to develop positive beliefs about the usefulness of that technology. Managerial commitment and support serves the key role of providing structures for the signification and legitimization of technology use. As observed by others (e.g., Compeau and Higgins 1995), it is important for technology implementers to assist individuals in developing positive perceptions about their ability to use the new technology. Finally, as suggested by Agarwal and Prasad
(1998), individuals who are personally more innovative in the use of information technology could be utilized as important change agents because they are likely to exhibit positive beliefs about technology use.