Tuesday, April 29, 2014


Jom dapatkan buku-buku berkualiti terbitan MPWS Rich Publication di :

Kuala Lumpur International Book Fair 2014 
( Pesta Buku Antarabangsa Kuala Lumpur 2014 )
Di booth yang bernombor 3006-3007
Dewan Tun Razak 3, PWTC  (berdekatan dengan eskalator dan cafe) 

24th April – 4th May 2014

Anda juga boleh dapatkan di 
MPWS Training Centre, 63-1, 63-2
Jalan Kajang Impian 1/11, Taman Kajang Impian, 

Seksyen 7, 43650 Bandar Baru Bangi, Selangor.

Banyak buku yang menarik menanti anda di sana antaranya : 
- Dialah Supervisorku

Tulis Tesis Cepat
- Mendeley Edisi Bahasa Melayu dan Bahasa Inggeris
- Zero Draft of Thesis Versi BM dan BI

Dan yang paling penting KAMI TERIMA BAUCAR BUKU 1 MALAYSIA!!
Jangan lepaskan peluang ini untuk mempertingkatkan mutu penulisan anda.


Thursday, April 24, 2014

Two Day Workshop on Structural Equation Modeling (SEM/AMOS) Level 1

Amos merupakan kependekan dari Analisis of Moment Structures yang digunakan sebagai pendekatan umum analisis data dalam Model Persamaan Struktural (Structural Equation Model) atau yang dikenal dengan SEM. SEM dikenal juga sebagai Analysis of Covariance Structures atau disebut juga model sebab akibat (causal modeling)

Dengan menggunakan Amos maka perhitungan rumit dalam SEM akan jauh lebih mudah dilakukan dibandingkan dengan menggunakan perangkat lunak lainnya. Lebih lagi penggunaan Amos akan mempercepat dalam membuat spesifikasi, melihat serta melakukan modifikasi model secara grafik dengan menggunakan tool yang sederhana.
Untuk mengetahui lebih lanjut, butiran untuk bengkel tersebut seperti dibawah:

Two Day Workshop on Structural Equation Modeling (SEM/AMOS) Level 1

25 & 26 April 2014 (Friday & Saturday)
8.30 a.m. - 5.30 p.m.
MPWS Training Centre, 63-1, 63-2, Jalan Kajang Impian 1/11,
Taman Kajang Impian, Seksyen 7, 43650 Bandar Baru Bangi, Selangor # map
Associate Professor Dr. Zainudin Hj Awang
RM400 (normal rate)
http://postgraduateworkshop. com/semlevelone

Untuk pendaftaran dan maklumat lanjut, sila ke link berikut:

Sunday, April 20, 2014

Your Research Tips: Rasch Model: Simply Easy to Make a Measurement & Assessment

Rasch Model: Simply Easy to Make a Measurement & Assessment!

Rasch Model can be applied to assessments in a wide range of disciplines, including health studies, education, psychology, marketing, economics and social sciences.

Many assessments in these disciplines involve a well defined group of people responding to a set of items for assessment. Generally, the responses to the items are scored 0, 1 (for two ordered categories); or 0, 1, 2 (for three ordered categories); or 0, 1, 2, 3 (for four ordered categories) and so on, to indicate increasing levels of a response on some variable such as health status or academic achievement.

These responses are then added across items to give each person a total score. This total score summarise the responses to all the items, and a person with a higher total score than another one is deemed to show more of the variable assessed. Summing the scores of the items to give a single score for a person implies that the items are intended to measure a single variable, often referred to as a unidimensional variable.

What is Rasch Model?
The Rasch model is the only item response theory (IRT) model in which the total score across items characterizes a person totally. It is also the simplest of such models having the minimum of parameters for the person (just one), and just one parameter corresponding to each category of an item. This item parameter is generically referred to as a threshold. There is just one in the case of a dichotomous item, two in the case of three ordered categories, and so on.

Working in Quantitative Data Analysis? So What?
The Rasch model, where the total score summarizes completely a person's standing on a variable, arises from a more fundamental requirement: that the comparison of two people is independent of which items may be used within the set of items assessing the same variable. Thus the Rasch model is taken as a criterion for the structure of the responses, rather than a mere statistical description of the responses.
For example, the comparison of the performance of two students' work marked by different graders should be independent of the graders. In this case it is considered that the researcher is deliberately developing items that are valid for the purpose and that meet the Rasch requirements of invariance of comparisons.

Analyzing data according to the Rasch model, that is, conducting a Rasch analysis, gives a range of details for checking whether or not adding the scores is justified in the data. This is called the test of fit between the data and the model. If the invariance of responses across different groups of people does not hold, then taking the total score to characterize a person is not justified. Of course, data never fit the model perfectly, and it is important to consider the fit of data to the model with respect to the uses to be made of the total scores.

If the data do fit the model adequately for the purpose, then the Rasch analysis also linearises the total score, which is bounded by 0 and the maximum score on the items, into measurements. The linearised value is the location of the person on the unidimensional continuum - the value is called a parameter in the model and there can be only one number in a unidimensional framework. This parameter can then be used in analysis of variance and regression more readily than the raw total score which has floor and ceiling effects.

Why undertake a Rasch analysis?

  •   A researcher who is developing items of a test or questionnaire intending to sum the scores on the items can use a Rasch model analysis to check the degree to which this scoring and summing is defensible in the data collected. For example, if two groups are to be compared on the variable of interest (e.g. males and females), it is important to demonstrate that the workings of the items is the same in the two groups. Working in the same way permits interpreting the total score as meaning the same in the two groups.
  •   In checking how well the data fit the model, it is important to be able to diagnose very quickly where the misfit is the worst, and then proceed to try to understand this misfit in terms of the construction of the items and the understanding of the variable in terms of its theoretical development.
  •   A very important part of the Rasch analysis from this perspective is to be in dynamic and interactive control of an analysis and to be able to follow the evidence to see where the responses may be invalid.

(Sources: http://www.rasch-analysis.com/rasch-measurement.htm)

Our next workshop. Don't miss it!

19 & 20 May 2014 (Monday - Tuesday)
8.30 a.m. - 5.30 p.m.
MPWS Training Centre, 63-1, 63-2, Jalan Kajang Impian 1/11,
Taman Kajang Impian, Seksyen 7, 43650 Bandar Baru Bangi, Selangor # map
Dr. Akbariah Binti Mohd Mahdzir
Registration Fee
RM300 (early bird rate) / RM400 (normal rate)

Monday, April 14, 2014


DEA is a relatively new "data oriented” approach for evaluating the performance of a set of peer entities called Decision Making Units (DMUs), which convert multiple inputs into multiple outputs. The definition of a DMU is generic and flexible. In recent years, there have been a great variety of applications of DEA in evaluating the performances of many different kinds of entities engaged in many different activities, in many different contexts, and in many different countries.

These DEA applications have used various forms of DMUs to evaluate the performance of entities, such as hospitals, US Air Force wings, universities, cities, courts, business firms, and others, including the performance of countries, regions, etc. Because it requires very few assumptions, DEA has also opened up possibilities to be used in cases which have been resistant to other approaches because of the complex (often unknown) nature of the relations between the multiple inputs and multiple outputs involved in DMUs.

As pointed out in Cooper, Seiford and Tone (2000), DEA has also been used to supply new insights into activities (and entities) that have previously been evaluated by other methods. For instance, studies of benchmarking practices with DEA have identified numerous sources of inefficiency in some of the most profitable firms – firms that had served as benchmarks by reference to this (profitability) criterion – and this has provided a vehicle for identifying better benchmarks in many applied studies. Because of these possibilities, DEA studies of the efficiency of different legal organization forms such as "stock" vs. "mutual" insurance companies have shown that previous studies have fallen short in their attempts to evaluate the potentials of these different forms of organizations. Similarly, the use of DEA has suggested reconsideration of previous studies of the efficiency with which pre- and post-merger activities have been conducted in banks that were studied by DEA.

If we want to learn and gain more and more knowledge, we won't wait for it but we have to grab the opportunity. I would like to suggest one workshop that can help you to gain knowledge in DEA and Panel Data, which will be conducted by an experienced speaker and you will not regret it.

The workshop details are as stated below:

Date: 21 & 22 April 2014 (Monday & Tuesday) 
Time: 8.30 am – 5.30 pm
Venue: MPWS Training Centre, Seksyen 7, Bandar Baru Bangi, Selangor
Speaker: Professor Dr. Fadzlan Sufian
Medium: English
More details : http://postgraduateworkshop.com/deapaneldata/

Monday, April 7, 2014

Bengkel Sehari Penulisan Pantas & Pengurusan Artikel


Jangan terlepas menyertai bengkel yang kami anjurkan :

Course Title: Bengkel Sehari Penulisan Tesis Pantas dan Pengurusan Artikel
Date:26 April 2014 (Saturday)
Time: 8.30 a.m. - 5.30 p.m.
Venue: Dewan Kuliah 1, Fakulti Kejuruteraan Pembuatan, 
Universiti Malaysia Pahang, 26600 Pekan, Pahang Darul Makmur
Speaker: Dr. Othman Talib
Registration Fee: RM180
Medium: Bahasa Malaysia