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Negative Influences on Research Quality – Analyzing Selection Bias in Research

Negative Influences on Research Quality – Analyzing Selection Bias in Research

Selection bias is a general term describing situations where bias is introduced into the research from factors affecting the study population. Selection bias occurs when individuals or groups in a study differ systematically from the population of interest leading to a systematic error in an association or outcome.

 Common types of selection bias in research

Researchers may unintentionally introduce selection bias into a study if participants differ from the target population in ways that affect the results. For example, if a survey is conducted solely on males, then any associations observed will be due to the gender differences between participants and target population, rather than to any inherent differences between men and women. There are two main types of selection bias in research: sampling bias and non-sampling bias. – Sampling bias happens when the study sample does not represent the population of interest. For example, a survey of all university students will very likely be skewed towards students who are more likely to participate in any survey, and so may not represent the people who would have their opinion changed by the results of the survey. This can be reduced by using a stratified sample of participants, or by using a sample that is representative of the target population. – Non-sampling bias happens when the research environment affects the results of the study, either inadvertently or intentionally. For example, a researcher may use a particular method or analyze a dataset in a way that leads to an association that is not necessarily representative of the population of interest. This type of bias can be particularly difficult to identify, as different researchers can often produce different results when using the same dataset.

Identifying Selection Bias in Research

There are many ways to identify selection bias in research, but the most straightforward is to look carefully at the methods and results of a study and see if they describe the target population. This is often done by comparing the results of a study to the demographics of the participants. If a study of university students shows that the participants are disproportionately more likely to be female, or have a lower socioeconomic status, there is a strong possibility that selection bias is occurring. Another way to identify selection bias is to examine the process that led to the study being conducted. If a survey was requested by a particular organization or with a particular goal in mind, then it is likely that the sample was chosen to support the chosen outcome. Selecting a sample in this way may introduce selection bias, although this is often more difficult to identify than sampling bias due to the subtle nature of the process.

Confusion about Confounding and Bias

While these two terms are often used interchangeably, selection bias is different from confounding bias. Selection bias occurs as a result of factors that affect the selection of participants, while confounding occurs as a result of factors that affect the results of the study itself. For example, a study that shows that males are less likely to support a certain policy than females may have a confounding variable, such as the fact that males are often less likely to support certain policies in the first place. However, this is not a case of selection bias, as the factors affecting the study sample (sex, age, socioeconomic status, etc.) are not the factors that affect the participants of the study.

Ways to avoid selection bias in research?

These methods can be used to reduce the risk of selection bias in research, although they are not foolproof. – When conducting a survey, attempt to make the sample as representative as possible of the target population. This can be difficult, as many people in a population are not likely to participate in a survey. To improve the likelihood of a representative sample, try to include people from as many demographic groups as possible, including people who are underrepresented in other surveys. – When reviewing datasets, try to identify when variables were chosen (or when they were not) to create the study dataset. This could help identify when non-representative variables may have been used unintentionally. – When designing a study, try to identify all the potential sources of selection bias. This will help to identify ways to reduce the risk of selection bias.


Selection bias occurs when researchers intentionally or unintentionally select participants who differ systematically from the target population, leading to incorrect conclusions. This bias can be reduced by careful selection of participants, careful data analysis, and careful design of a study. It can also be reduced by careful consideration of the factors that affect the way that participants are selected to participate in a study. Se selection bias in research happens when researchers unintentionally or intentionally select participants who differ systematically from the target population, leading to incorrect conclusions. This bias can be reduced by careful selection of participants, careful data analysis, and careful design of a study. It can also be reduced by careful consideration of the factors that affect the way that participants are selected to participate in a study.

Real World Setting – Using Grounded Theory for Qualitative Research

Real World Setting – Using Grounded Theory for Qualitative Research

Qualitative research is a research method that focuses on in-depth analysis of the experiences, perceptions, and attitudes of people in a particular setting. Qualitative researchers are interested in studying human experience and behavior. They try to understand the meaning and significance of events through close observation and analysis of people’s experiences. 

Situating grounded theory

Grounded theory is a complex methodology, it refers to a set of systematic inductive methods for conducting qualitative research aimed toward theory development surrounding a social issue. It is quite often used to provide explanations to phenomena that do not have any theoretical background. The basic idea behind grounded theory is that you should start with your data and then develop your theory from there. You don’t try to make up a theory in order to test it; instead, you try to develop your theories based on what you learn from your data. 

Grounded theory is a qualitative approach in research that emphasizes inductive, reflexive and participatory research. Grounded theory is a way of doing qualitative research that involves the process of generating hypotheses and then testing them by inductively collecting data from participants. As you go through the process of generating hypotheses, you will begin to understand how people think about their experiences in new ways; this understanding can lead to new ideas about what has been happening in your study.

The term “grounded theory” was coined by Glaser and Strauss (1967). The purpose of grounded theory is to generate an integrated explanation or model from observed phenomena (Glaser & Strauss, 1967). The development of grounded theory requires researchers to engage in an iterative process: 

  • First, they develop general concepts based on their observations; 
  • Second, they refine these concepts using additional data; 
  • Third, they test these refined concepts against other theories and apply them as necessary.

The goal of grounded theory is to develop an understanding of the meaning of a phenomenon, which can then be used in subsequent research. The process involves developing a theoretical model based on the participant’s own experiences and interpretations, rather than using an existing model from other researchers.

Grounded theory design and significance

Qualitative researchers begin their analysis by describing participants’ experiences with their feelings about what is happening around them. They then try to understand how those feelings influence the way they view themselves as well as others in their life situations. Typically, qualitative researchers will not use any form of quantitative data collection such as questionnaires or statistical surveys as part of their research process because they believe that the answers provided by these methods are too generalized to accurately portray the individual’s true thoughts and feelings. Instead qualitative researchers rely upon open-ended questions which allow participants to formulate their own responses without being influenced by any preconceived ideas or expectations about responses that might have been held by researchers prior to conducting the interview session. 

Similarly, in grounded theory, theoretical sampling is a key aspect of the sampling stage of grounded theory. Participants are recruited based on their different experiences of a phenomenon and the information is collected using observation, literature survey and focus groups and interviews. This form of data collection is iterated with key relationships and analysis formed with each step. Its significant strengths include (a) presents clear, sequential steps for doing qualitative research; (b) provides specific methods for processing the data analysis phases of research; (c) unifies data collection and processing; (d) explores the theory of qualitative data; and (e) legitimizes qualitative research as scientific enquiry.

The qualitative researcher tries to understand people’s experiences by collecting data from multiple sources such as interviews and observations. This type of research involves collecting data from individuals who are directly involved in an issue or event being studied. Consequently, this type of research can be used to study a wide range of subjects including social issues such as prejudice and discrimination, personal development and growth, group dynamics and leadership styles, educational issues such as teaching methods and techniques, etc.

The main advantage is that it helps researchers create a better understanding of their subjects’ experiences and behaviors by focusing on them holistically instead of focusing on specific events or items (Bryman & Bellah

Limitations and issues of validity

Limitations or weaknesses of grounded theory:

1) It can be time-consuming because you must spend time doing ethnographic fieldwork in order to generate your data set (this can be especially difficult if you only have limited resources).

2) Your findings may not be generalizable because your sample size may not be large enough for you to draw conclusions about larger populations.

Grounded theory is also limited by its lack of validity, meaning that it cannot be used to make predictions about future events or situations.Corbin and Strauss (1990) explained that in order to comprehend the degree of validity of grounded theory as a qualitative tool of investigation, alterations need to be made in the framework illustrating the construct of validity.

Another limitation of grounded theory is that it is not a “scientific” approach to qualitative data. The intent of the method is to develop a theory based on the data and then incorporate that theory into a research article. The resulting article may not be as rigorous as an original study by itself, but it will be a more complete picture of what has been learned.

The weakness in this approach is that the researcher does not have control over how the data will be used or what conclusions will be drawn from them. This means that there is no way to determine if certain information has been missed or misconstrued by using this method.

One of the most important limitations of grounded theory is that it cannot be used to study the same topic in different settings. For example, if a researcher wants to study how women feel about maternity leave policies in a particular company, he or she would have to use data collected from interviews with employees and managers at that company. However, this approach would not work if the researcher wanted to use data from interviews with employees and managers in other companies.

Another limitation of grounded theory is that it does not allow for inductive reasoning. This means that one cannot draw conclusions from observations or from data collection (Heelan, 2011). To illustrate this limitation, consider an example where a researcher collects data on how many customers are satisfied with their purchases from a store. This information could be used as evidence for whether or not the store should increase their prices, but it cannot be used as evidence for what should happen next (Heelan, 2011). 

PhD Topic Ideas: A 10 point rule book to develop your original yet viable PhD topic

PhD Topic Ideas: A 10 point rule book to develop your original yet viable PhD topic

If you the one reading this blog, it is likely that you are wanting to enroll for a PhD programme but still struggling with the topic selection for your PhD thesis. It isn’t as straightforward to find the most appropriate topic for your research as you may perceive it to be. But if you have the right attitude and the required patience, then surely you would be successful.

There are a certain set of rules that you must follow if you want to ensure that you choose the right research topic.

  1. Before making the final decision, you must read a lot of dissertations that are linked to your subject or your key interest areas. It would familiarise you with different ideas and research styles. It would not only help you to zero down on a topic but also give you a multidimensional outlook and later help you to devise your research style.
  2. Make sure you look for a topic that interests. Listen to the advice of your professors but go with the choice that is entirely yours.
  3. Get back to old ideas. Check old resources you might have used any time in your graduation years and try to see if some evolution could be done on them.
  4. Consider several ideas rather than looking for that one perfect idea. At the initial stage, you must have a welcoming approach to even the craziest ideas. Think of as many ideas as you can. It would eventually bring you closer the topic you have been looking for your research.
  5. Before finalising on a topic, ensure that nobody has completed a similar research. Collect supporting arguments why your research matters. It would help to keep you convinced and at the same time to convince your supervisor and examiners at the later stages.
  6. Assess the need for resources and information for the research. Make sure you have done a thorough analysis of the needed resources and information for the entire research to be conducted and surety that you have access to all of that.
  7. Have a precise and succinct topic. Usually, researchers who begin their PhDs with over ambitious projects struggle at the latter stages.
  8. Have a flexible perspective to your main research question as it may change during the course. Be flexible as you can so that you can quickly adapt to new evidence.
  9. Take expert opinion with your supervisor while you are deciding as they can give you a practical perspective to the obstacles and challenges that may come at the subsequent stages, which you may not be able to anticipate.
  10. Listen to your heart and be ready to fall in love with your topic.

Always know that, even after having decided the topic very cautiously, there would be moments when there would be a feeling of saturation and exhaustion with your topic. Do not feel dejected and know that it is common and part of the process.

Does Every PhD Research Require a Conceptual Framework?

Does Every PhD Research Require a Conceptual Framework?

A majority of reports indicates that over 89% of research candidates find it difficult to decide if their research requires a conceptual framework or not.

Are you fighting the same battle?
If yes, then this article will surely help you out!

The conceptual framework is an essential ingredient for your research. It provides a glance on researcher’s synthesis of literature on how to explain a phenomenon.

The requirement of a ‘Conceptual Framework’ depends on the type of research. But before explaining which research requires a conceptual framework, let me first tell you what purpose a conceptual framework fulfils:

  1. It generates proper links from the literature to the questions and research goals.
  2. It serves as a medium to keep research on track.
  3. It provides a clear insight on the variable of a study.
  4. It explains the concepts and proposes the relationships among the concepts.
  5. It provides an organized structure for the research design and methods.
  6. It guides the development & testing.
  7. It represents the relationship of the developed hypothesis with central factors or key concepts.

Now, moving towards the purpose of this article, let’s see, which research requires a conceptual frame:

A conceptual framework is understood as an explanation of how a research candidate sees the different concepts and outcome of the study and its relation with each other. It can be an adoption used in a previous study with modification to suit the inquiry.


A research can be categorised into two types mentioned below:

  • Exploratory Research: It is also known as formative research, its objective is to gather preliminary information that will help define problems and suggest hypothesis. It is conducted for a problem that has not been clearly defined. Exploratory research helps determine the research design, methods of data collection and conceptual framework.
  • Explanatory / Casual Research: Casual research is quantitative in nature. It is pre-planned and structured in design that’s why it is also known as conclusive research. It is different from exploratory research in terms of explaining cause and effect relationship between variables. Explanatory research shows the cause and effect relationship in terms of experiments and doesn’t require a conceptual framework.

There are two research methods for exploring the cause and effect relationship between variables:

  1. Experimentation
  2. Simulation

What if your research requires a conceptual framework?

Well, don’t worry; we have got your back.

But, what all do we require for developing a conceptual framework?

Below are the ingredients required for developing a conceptual framework:

  1. Literature Review
  2. Knowledge of specific research domain
  3. Research Background
  4. Personal Experience
  5. Data

We understand that the conceptual framework is a prominent document for your research. Let’s discuss how to develop a conceptual framework.

Developing a Conceptual Framework:


  • Identify Concepts:

Identify concepts from the literature review and provide a categorization among them. The concepts can be categorised as abstract or concrete.

An abstract concept is broad and may not be readily observable while the concrete or specific concepts are amenable to measurement.’

  • Define Variable:

Defining variable is the main function of a conceptual framework in a descriptive research. A variable is something that changes. The change in variable depends upon the various factors; some of the variables are like constant only (name of someone) while other change frequently (Value of Stock Exchange)

  • Operationalize Variables:

The operationalization of variables involves strictly defining variables into measurable elements. It defines fuzzy concept and allows them for empirical and quantitative measurement. To improve the robustness of research design and to increase the quality of the result, operationalization of variables sets down the exact definition of each variable.

  • Develop Propositions:

Develop the relational statement or propositions among the concepts. This helps in providing an idea for hypothesis development and testing.

  • Explore the relationship between variables:

Exploring the relationship among variable is an important part of developing a conceptual framework. Some research abstracts contain the variable of research and thus may serve the purpose.

Even though conceptual framework is the heart of a research, not every research requires a conceptual framework.

Do you require assistance in developing a conceptual framework? Then drop a mail at!

Design of Research Questions

Design of Research Questions

Devoid of coming up with concrete research question(s), any research based study can never be started. Based on observational phenomenology, a broad research objective is formed, and then through epistemology and construct building, the research objective is boiled down to concrete research question(s). Unless those research questions are not specific and measurable, the research work can never be effective in all aspects. Specificity of the research question is required in order to keep the study focused. There are several organizations, which assist researchers in designing research questions for their studies. For more information about designing research questions, kindly go through the pages of

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