Research Design : strategy for women Ph.D. scholars currently working as associate / assistant professors in India

Research design is a creative process rather than a research process and thus requires both theoretical knowledge and its application.

1. Hypothetico - Deductive model: this model follows an approach where design focus lies on starting with an hypothesis and using deductive step by step reasoning to either confirm the said hypothesis or reject it. The design is such that every possible scenario which could become a hindrance in accurately deducing the confirmation of starting hypothesis has an extremely low probability of occurrence.
2. Decisional / action / applied research: in this research application, the researcher does not focus on developing a generalized theory for a research phenomenon but instead relies on specific application of a generalized theory to her specific research setting. Therefore, the design follows controlling only those factors or variables which may apply to your specific research setting while the broader variables are left uncontrolled.
3. Current stage of research progression: based on your chosen type, exploratory research design would be such that all and possibly new factors are uncovered explaining a phenomenon under investigation and therefore focus more on data collection, an analytical research design would focus more on data analysis, explanatory research design would centre its focus on causation aspects and finally evaluation research design would be primarily focussed on all three.
4. Quantitative phenomenon: A research design investigating a quantitative phenomenon is heavily focussed on numbers and their meaning starting from research setting to final conclusion.
5. Data collection: observational research design focusses on reducing researcher biases whereas experimental research design focusses on reducing confounding variables and biases both.
6. Key information sources that will be used for research: When using secondary data for your research, the research should specifically focus to standardize data to fit the current research setting, therefore, research design should focus on defining settings and variables their analysis and the conclusions derived from this and how already available data satisfies various conditions of the current research settings. However, when using primary data, in addition to the aforementioned, it is also important for the design to consider answering the question "as to how the researcher was collecting only that data that she intended to do?".
7. Ways in which causal relationships will be researched: As already mentioned in the research type article, you should consider a design which enables you to describe, correlate, compare and then make inferences about various related relationships existing in the phenomenon of your research interest.
8. Relationship of time with the current research: In a retrospective research you would not be able to control the research setting by physical means so the research design is easier as there is minimal research setting, thus the research design follows an approach of defining the set of conditions that were prevalent at the time of data collection. However, for both cross-sectional and longitudinal studies the design focus is to have consistent research settings and minimal amount of variation within it during and between data collection events.
9. Type of investigation that would be carried out for the research: The research design for various types of research within this category differ in its selection of unit of research and thus the unit of analysis and how this unit forms a part of the larger and broader investigation of research.

1. Validity: Internal i.e. accurate identification of causal relationships and the effects of errors due to selection bias, history effects, participants & instruments on the same; External i.e. generalizability of findings and the effects of errors due to sample characteristics, research settings & research conditions on the same; Construct i.e. accurate measurement of intended concept and the effects of errors due to measurement tools, operational definitions & conceptual framework on the same; Content i.e. ability of the instrument to measure the entire range of construct and effects of expert judgement on the same; Lastly, Criteria validity i.e. how accurately a test measures the outcome it was designed to measure and effects of standardization and pilot testing on the same. You should try to design your research in such a way that it increases the validity of your research.
2. Reliability: refers to the consistency of a research method in producing stable and consistent results. Firstly, Internal consistency ensures that items within a test or measurement tool yield similar results. Secondly, test-retest reliability measures stability over time by administering the same test to the same subjects at different times. And lastly, inter-rater reliability assesses the degree to which different raters or observers give consistent estimates of the same phenomenon. Reliability is necessary but not sufficient for validity. A reliable measure can still be invalid if it doesn't measure what it intends to. In order to increase the overall reliability of your research try to first use standardized procedures and instruments, if these are not available then pilot test instruments to identify potential issues before the main study.
3. Errors: in research design can undermine the validity and reliability of findings. Selecting a sample that is not representative of the population can lead to skewed results. This includes convenience sampling or self-selected samples. Too small a sample can increase the margin of error and reduce the ability to detect significant effects. Using tools or questionnaires that lack validity or reliability can produce inaccurate data. ague or poorly worded survey items can lead to misinterpretation and inconsistent responses. Failing to control for confounding variables can result in misleading conclusions. These variables may affect the dependent variable, obscuring the true relationship. Without random assignment in experimental designs, results may be influenced by pre-existing differences among participants. Not having a control group or using a weak control can compromise the ability to attribute effects to the treatment. Using inappropriate statistical tests can lead to invalid conclusions. This includes misapplying tests or failing to meet their assumptions. Poorly defined research questions or hypotheses can lead to vague objectives and results that are difficult to interpret. Drawing broad conclusions from limited data or specific populations can misrepresent the findings. Addressing these potential errors during the design phase of the research can enhance the rigour of your research and the reliability of its findings.
4. Bias: refers to systematic errors that can affect the validity and reliability of study findings. Key is to reduce various bias like selection, measurement, confounding, observer, publication and attrition. To minimize bias, you can use randomization, blinding, stratified sampling, and rigorous data collection methods, along with transparent reporting practices.
5. Variables: When designing research, carefully considering variables is crucial for ensuring valid and reliable results. Consider evaluating as to which variables belong to which category (Independent, dependent and confounding). Define operationally as to how each variable will be measured or manipulated. Consider the expected relationships between variables. Conduct power analysis of previous studies related to your topic to estimate a sample size and confirm that sample size through a pilot study. Plan for how variables will be analysed statistically. Choose appropriate methods based on the types of variables and their relationships.

Additional Resources:

• About Ankit Gupta

• CrossTab PhD Thesis Advisor

Person > Name: CrossTab : Er. Ankit Gupta (B.E. & P.G.D.M.) | Job-title: Research Advisor and Consulting Statistician | Address: Dehradun, Uttarakhand, 248001, India | email: mail@ankitgupta.net.in, Telephone: +919557561661 | About, Linkedin, Github, Gravatar, Kaggle, CV, Google Listing, Quora, X, ORCID 

Organization > Name: CrossTab | Description: Research Advisor and Consulting Statistician | Address: Dehradun, Uttarakhand, 248001, India | email: mail@ankitgupta.net.in, Telephone: +919557561661, CrossTab : Er. Ankit Gupta (B.E. & P.G.D.M.) | Logo, Image, Phd Thesis Advisor, Datalytics

Local Business > Type: Professional Service | Name: CrossTab PhD Thesis Advisor | Address: Lane 2, Chaman Vihar, Niranjanpur, Majra, Dehradun, Uttarakhand, 248001, India | email: mail@ankitgupta.net.in, Telephone: +919557561661, CrossTab : Er. Ankit Gupta (B.E. & P.G.D.M.) | GeoCoordinates: 30.303136222481026, 78.00547703936927 | openingHours: Mo, Tu, We, Th, Fr, Sa, Su 18:00-20:00 |  Logo, Image, CrossTab Phd Thesis Advisor, Linkedin

Local Business > Type: Professional Service | Name: CrossTab Datalytics | Address: 31, Arhat Bazar, Dehradun, Uttarakhand, 248001, India | email: mail@ankitgupta.net.in, Telephone: +919557561661, CrossTab : Er. Ankit Gupta (B.E. & P.G.D.M.) | GeoCoordinates: 30.317078177080585, 78.03011853936965 | openingHours: Mo, Tu, We, Th, Fr 09:00-17:00 |  Logo, Image, CrossTab Datalytics, Linkedin