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A Simplified Comparison of the Key Study Designs

Cross Sectional Study Design: The use of cross sectional design is used for the kind of research that collects data on more relevant variables at a single attempt from different kinds of people, subjects or phenomenon. The key feature here is that the data is collected at the same time.  The cross sectional design offers … Continue reading “A Simplified Comparison of the Key Study Designs”

Cross Sectional Study Design: The use of cross sectional design is used for the kind of research that collects data on more relevant variables at a single attempt from different kinds of people, subjects or phenomenon. The key feature here is that the data is collected at the same time.

 The cross sectional design offers a snapshot of the different variables in the study. It would help to bring forth those variables that are representatives of a cross section of the population. These designs usually depend upon the survey techniques for the collection of data.

Cross Sectional Study Design have key advantages and disadvantages.

The main advantages are:

  •  It collects data on multiple variables
  • Data is collected from a large number of respondents
  • Data is collected from varied subjects
  •  It collects data on attitudes and behaviour
  • It aids exploratory  research
  • It helps to generate relevant hypotheses for future research
  •  The data from this is useful for many different researchers

The main Disadvantages are:

  • Augments chances of error
  • Adds the cost as the subjects increase
  • Increases cost as there are multiple locations
  • Does not measure or evaluate change
  • Does not focus on cause and effect
  • It does not control independent variable
  • It is more time bound

Longitudinal Designs

As the name is indicative, a longitudinal design collects the data over a span of time. The measurement is taken on each and every variable in not just one time frame but over two distinct times. It aids in measuring change and comparing it over time. Time series and panel are two different types of longitudinal designs.

When we talk of the first type, a Time Series Design compiles the data on a similar variable at predefined regular intervals.  This is done in a form of aggregate measures of population. There are a lot of uses of Time Series Designs.

  • Putting up a baseline measure
  • Comparing the changes that have taken place over time
  • Keeping a record of the trends
  • Predicting trends for the time to come

The presentation of Time Series data is in the form of pictorials like charts and graphs. Analysis and interpretation from these graphs looks for four types of patterns that are identified.

  • Long term trends
  • Cyclical Variations
  • Seasonal Variations
  • Irregular Variations

There are some advantages and disadvantages of Longitudinal Designs. These are:

Advantages:

  • It is very easy to collect data
  • Representation of data in graphs is easy
  • Interpretation of data is easy
  • It is useful for prediction of short term trends

Disadvantages:

  • The approach for data collection changes over a time period
  • It is difficult to bring out more than one variable at a certain time
  • It needs to be clubbed with qualitative research for explanations
  • It relies on the assumption that present trends will remain unchanged

Is there a crisis we are facing with smart phone research?

The word “Mobile” is the most commonly used word we see around. It is able to put research in a context which has not been understood before. It provides a whole lot of advantages that researchers have been seeking for ages in order to bring in the accuracy in their analysis and better responsiveness. It … Continue reading “Is there a crisis we are facing with smart phone research?”

The word “Mobile” is the most commonly used word we see around. It is able to put research in a context which has not been understood before. It provides a whole lot of advantages that researchers have been seeking for ages in order to bring in the accuracy in their analysis and better responsiveness. It brings in the idea of just in time feedback and brings in the synergy between the respondent and the researcher even if they are at different locations. Of course, mobile research has grown but it is thought provoking that why it has not boomed?

Research a has revealed that mobile device surveys are on a constant rise but at the same time the dropout rates for smartphones are almost twice. Respondents have been seen using mobile devices as medium for easy participation in research. However, a significant barrier in mobile research completion is the difference in the screen size and the variation in the ease of data entry. It is important in this phase that the screen size, the functions of data entry and the length of the survey should have the flexibility to fit into the situation of the respondent and not just the need of the respondent.

The research fraternity needs to appreciate the ease and comfort with which the respondents use the smart phone devices. In this learning process of smart phone adaptability in research the researchers are learning to overcome the barriers and finding means to squeeze out meaning and value out if shorter mobile texts. There are certain tips that researchers could follow in order to stay ahead in this trend:

  1. Do not resist but respond to change
  2. Customize and offer alternatives for technology involved research by giving options for desktops/mobiles and smart phone alternatives.

The feasibility of technology is all about the tipping points. In time to come, the mobile access of research would actually reach a point where the researchers would have  no choice  but to accept the change. The question that is triggered in each one’s mind is whether research would be able to accept and adapt to the methods and acceptations that are changing or they would remain stuck with the expected but unacceptable dropout rates?

 

Individualities of Destructive and Useful Questions

Individualities of Destructive Questions: Researchers are often found suggesting guidelines for creative research supportive questions. However, before doing that it is important to clearly know, what are the kinds of questions that need to be avoided.  There are certain kinds of questions that can be called as destructive questions for a questionnaire. They have their … Continue reading “Individualities of Destructive and Useful Questions”

Individualities of Destructive Questions:

Researchers are often found suggesting guidelines for creative research supportive questions. However, before doing that it is important to clearly know, what are the kinds of questions that need to be avoided.  There are certain kinds of questions that can be called as destructive questions for a questionnaire. They have their own traits and it is important to identify those traits.

  1. Stay away from questions from basic Yes, No questions. The reason being that they offer a very little understanding of the direction these questions take the research into. The focus of the researcher should be to pink up questions that begin with interrogative words such as, What, How, When, Where.
  2. Questions should avoid the use of any leading terminology. They take the response of the respondent in a predefined direction and are often taken in the category of being manipulative or dishonest questions.
  3. Do not have too many questions that begin with, “Why”. These questions bring up a feeling of defensiveness in the respondent and they may get offended that their actions need to be justified to the researcher.

 Individualities of Useful Questions:

These set of guidelines may be helpful in creating a more responsive, analytical and fair questionnaire.

  1. Incorporate open ended questions wherever it is possible. These kinds of questions go beyond the conventional yes or no. The advantage is that they generate a thinking process for the respondent and keep his focus on the questionnaire.
  2. In the case of an interview session, with open ended questions, do ask clarifying questions so as to get an understanding of the bottom line.
  3. Try to bring in questions that give an understanding about the perspectives, assumptions and actions of the respondent.
  4. Ask for help and ideas. It can serve as a powerful tool when enough faith is shown in peer or at times even the respondent when you ask for help. It may help you to get a fresh insight into the research. You could get clues by putting up enquiries such as, “What questions should I be asking now?” or “What else can I know from you?”

How do I Choose a Statistical Software

The world around is talking about data analysis. Whether one talks about analysis of consumer behaviour or a perspective to the critical metrics of six sigma or maybe any other programme that is actually data driven it is all related to data analysis. The good news here is that not only is the available data … Continue reading “How do I Choose a Statistical Software”

The world around is talking about data analysis. Whether one talks about analysis of consumer behaviour or a perspective to the critical metrics of six sigma or maybe any other programme that is actually data driven it is all related to data analysis. The good news here is that not only is the available data more than ever before but there are available an enormous range of software options which simplify the understanding of the data which otherwise is difficult to comprehend.

The options that are available for data analysis have a large gamut of options available. They range and vary from paper pencil option to a calculator to a more customized system that would very precisely take care of the smallest of detail tailored as per the needs of the researcher. However they would cost much more than the conventional systems and could go up to millions of rupees.

Talking of the extreme ends of the gamut, unless the researcher really enjoys calculations on fingers or has a huge amount of money lying idol to splurge, a software package sitting somewhere between these two extremes  is what would work the best. However, that still leaves the researcher a wide variety of software packages to choose from and one needs to administer in a research.

When one talks about picking up data analysis software, there isn’t any right or wrong choice. What works best for a particular researcher may depend on more than one factor.

The first factor to consider is to analyse the person who will be using the software. The statistical skills of the person in terms of, whether he is an expert, novice or a blend of both. Will the data be analysed day in day out or once in a while? When this is figured out, it helps to match options with needs so as it can be avoided to choose any wrong package  that is either too difficult to handle or does the wrong thing entirely

Comparison of Data Types

It is vital you pick approach research methodologies and methods for your thesis – your research after all is what your whole dissertation will rest on. When the researcher is willing to collect quantitative data it means that the variables are being measured and existing hypotheses are being verified and questioned. Often data is used … Continue reading “Comparison of Data Types”

It is vital you pick approach research methodologies and methods for your thesis – your research after all is what your whole dissertation will rest on. When the researcher is willing to collect quantitative data it means that the variables are being measured and existing hypotheses are being verified and questioned. Often data is used to generate new hypotheses which are based upon data that is collected on different variables. If one would try to compare qualitative data with Quantitative data, it could be compared on the following parameters.

 

Goal or Aim: The aim of qualitative research is more exploratory in nature. It provides a more detailed description of the research topic. On the other hand, quantitative research is more focussed on counting and classifying the features that comprise statistical models and figures which target to explain the observation.

 

Usage: In the beginning phase of the research qualitative research serves a better purpose and when one talks about the latter part of the research, quantitative research has more weightage. A clearer picture about what to expect from research is drawn from quantitative research vis a vis qualitative research.

Data Gathering: In the case of qualitative research, the main data gathering instrument is the researcher. The different strategies that the researcher employs depend largely upon the approach of the research. Some of the examples of the techniques in qualitative research are in depth interviews, structured unstructured interviews, narratives etc. When one talks of quantitative research tools, the instruments used are questionnaires and surveys to collect numerical data which is measurable.

Presentation of the Data:  In the case where the data is of qualitative nature, in any of the forms such as words, images or objects, it appears in the form of graphical figures. On the other hand, if the research is quantitative in nature, the tabular representation of data is there which is in the form of numbers or statistics