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Quantitative & Qualitative Research - Science topic

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Hello, I've extracted RNA from A549 cells and I've done nanodrop to determin the RNA concentration. And then I meet the problem. I have no idea about the concentration and the quality of cDNA after doing reverse transcripataion.
I searched some information and know that I can make a stand curve to determin the concentration, but I don't have standard product.
I want to ask is there othre method to the concentration of cDNA with RT-qPCR. I have and idea about using internal control (like TBP), but I'm not very sure about how to connect the Ct value of TBP to the concentration of cDNA.
Hope someone give me advice!
THANK YOU
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The cDNA that you synthesized is for gene expression studies, so in such case, you should run comparative Ct protocol in RT-PCR for which you'll require house keeping genes as endogenous control. The Ct value of the endogenous control will be used to normalised your targetted gene, so no prior concentration of your cDNA is required.
Now if you want to analyze the yeild of your extracted RNA, you can run absolute quantification protocol using any known standards (now a days many standards are commercially available in some kits, like viral detection kit or NGS library quantification kits).
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I came across this idea that I've never heard of in the study of Li et al. (2023), just a brief context, it's a review on the relationship between epistemic trust and developmental psychopathology.
In their section of "Epistemic Trust and Mental Health". Their first few lines prompted my question of using a proxy measure, specifically they examined multiple studies which used a trust subscale as a proxy measure for epistemic trust. Therefore, I'm just wondering how would that work? It sounds like to me there's alot more disadvantages than advantages since you're using a slightly different variable, but of course, I might be very wrong on this so I welcome any new insights.
Ref: Li, E., Campbell, C., Midgley, N., & Luyten, P. (2023). Epistemic trust: a comprehensive review of empirical insights and implications for developmental psychopathology. Research in Psychotherapy, 26(3). https://doi.org/10.4081/ripppo.2023.704
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Using a proxy measure means using a related variable to indirectly measure the one you're interested in. This is often done when direct measurement is difficult.
For example, using the number of steps taken per day as a proxy for physical activity levels.
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Hello RG Family! In my transition to qualitative research, I’m confronted with the challenge of validating qualitative interviews.
From my knowledge of quantitative research, I’m well aware that Principal Component Analysis and Cronbach’s Alpha methods are popular for validity and reliability of Likert-scaled questionnaires. But in the case of qualitative interviews, the arena is different. That’s why I need your help.
From your wealth of experience with qualitative research, please describe the most effective methods for carrying out validity and reliability of qualitative interviews. And which software is suitable for this procedure?
Your contributions will be immensely appreciated. Thank you.
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In quantitative research, reliability and validity apply to concerns about measurement, but in qualitative research we do not measure anything, so reliability and validity are not nearly as relevant. Indeed, many qualitative researchers refuse to accept this terminology and you may find yourself in trouble with reviewers if you do use it.
The basic reasoning behind this is that qualitative research is inherently subjective and interpretive, so there is no reason to expect another researcher to come to the same conclusions. Commonly used alternatives (especially to validity) are trustworthiness and credibility.
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There's an increasing number of studies on the use of qualitative and mixed methods research in clinical trials but process of translating evidence from clinical trials to practice and policy remains problematic. Just wondering how qualitative and mixed methods could be used more effectively to facilitate translation.
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You could embed your mixed-methods approach to a clinical trial by utilising a process evaluation framework. For example with RCTs, when evaluating complex interventions, the MRC framework for complex interventions provides a framework upon which your trial methodology can be based. This is a rigorous process which includes the critical evaluation of trial findings but also considers evidence based trial protocol development, PPI involvement, trial team evaluation and generailsed recommendations. A nice example of this is by Cassarino et al (2022). See below. @
Cassarino M, Cronin Ú, Robinson K, Quinn R, Boland F, Ward ME, McNamara R, O'Connor M, McCarthy G, Ryan D, Galvin R. Development and delivery of an allied health team intervention for older adults in the emergency department: A process evaluation. PLoS One. 2022 May 26;17(5):e0269117. doi: 10.1371/journal.pone.0269117. PMID: 35617330; PMCID: PMC9135235.
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I read an article and was intrigued by their use of discourse analysis + computational methods to track word use associations. Does anyone know suitable primers for computational content analysis? Also, they use QDA Miner-WordStat, but it's only available on PC are there MAC versions available?
I'm hoping to supplement qualitative discourse analysis with content analysis.
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Are you thinking of machine learning and natural language processing? If so, conduct an academic search for both terms together. There is a learning curve.
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there are many statistics software that researchers usually use in their works. In your opinion, which one is better? which one do you offer to start?
Your opinions and experience can help others in particular younger researchers in selection.
Sincerely
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SPSS, as my results necessitate analysis using SPSS
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Hi! I am interested in collaborating. I study business analytics and AI.
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I want to inquire about various methods to prove the contingency perspective in social sciences.
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Hi,
The contingency theory of management proposes that the most effective style of management depends on the specific situation at hand. To prove this theory, researchers use various methods including: like case studies ,experiment , survey , interview , observations.
Regards,
Uday Bhale
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21 items 👉🏼 4 sub-constructs 👉🏼 1 construct
33 items 👉🏼 4 sub-constructs 👉🏼 1 construct
so there are three levels:
lower order 👉🏼 medium order 👉🏼 higher order
The results are significant. But tell me, can we squeeze these 21 and 33 items into above 2 constructs, respectively?
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You may start with measurement theory and theoretically establish your construct of interest. Also, check Chapter 1: https://www.smartpls.com/documentation/getting-started/pls-sem-book
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Hi everyone,
I am currently in the process of reviewing feedback responses from my pilot survey (mixed methods with a mixture of closed and open ended questions).
One of the feedback that I have received from many of the respondents was they would like to choose more options in the question that I have asked e.g. Describe the type of service delivery that you provide (please pick up to three).
For this type of question, I don't think forced choice or check all that apply would be appropriate and I am trying to prevent people from satisficing answers for CATA. Most clinicians (targeted population) work with a variety of clients and my goal here is to get them to pick top three that they spent the most time in. I am not looking for them to rank based on my research question but what I am looking for is to see certain relationship e.g. respondents working in the education department seemed to be more confident in x. So basically in my case, all the options provided are of equal standing and what I am just looking for is for them to pick 3.
As mentioned, many of the respondents want to pick more than 3 and I am not sure what number is appropriate. I have tried looking for guidance by reading research articles related to survey designs and nothing relevant seemed to come up.
Basically my question is: does anyone know of any research evidence behind these multiple selection questions (why only three can be chosen) and if there is some formula to decide how many options the respondents should choose based on the number of options provided (e.g. if there are 6 options on the response stem choose only 2, if 12 choose 4 etc? ). If there is an expert in this field that has done specific research in this - please let me know of their names and I will look them up.
Thanks in advance.
Gen
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There is no clear-cut formula or rule when it comes to determining the number of options respondents should choose in multiple selection questions. It ultimately depends on the research question, the targeted population, and the nature of the options being provided. Some studies may require respondents to choose only one option, while others may allow them to select multiple options.
However, there are some best practices that researchers can follow when designing multiple selection questions. For example, researchers should ensure that the options provided are mutually exclusive and collectively exhaustive. This means that each option should represent a unique and distinct category, and that all possible categories are included in the options.
In terms of limiting the number of options respondents can choose, researchers can consider providing a clear rationale for why only a certain number of options can be selected. This can be explained in the survey instructions or in a pre-survey communication with respondents.
Overall, the key is to design questions that are clear, concise, and relevant to the research question at hand, while also taking into consideration the needs and preferences of the targeted population.
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Although the preprints submissions can be interesting to check the repercussions, criticisms and suggestions pointed out, I think that a not very good choice of platform can have limited results. Among the platforms researched, I observed that OSF, Scielo and Elsevier preprints offer a reasonable structure for preprints submissions and analysis. In this sense, I kindly ask for suggestions on which platform may be the most indicated for a preprint submission in the field of social sciences.
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https://psyarxiv.com/ is common for psych, but if your goal is to get a lot of readers, with any of these it will be helped by posting links on social media. As since we are on ResearchGate, you can post here too.
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I would be so grateful to you if you would help me about some facts regarding the MCC, I would begin my dissertation on MCC, next year-2023. Thank you.
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And what is MCC?
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I do not want to analyze the text inside the book I just want to explore the existence of the main components.
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Can you look for themes? Sure. Thematic analysis can be used. Obviously your data can be "thin," but a well structured sample can improve validity and reliability. Often we think there's only Braun and Clarke, but Muir and Fereday provide a competing perspective. Boyatzis also used thematic analysis with documents. Here my recommendation: Be pragmatic. Thematic analysis is adaptable to most any situation. (Note Muir/Friday used thematic analysis with documents as well as Boyatzis.)
Fereday, J., & Muir-Cochrane, E. (2006). Demonstrating rigor using thematic analysis: A hybrid approach of inductive and deductive coding and theme development. International journal of qualitative methods, 5(1), 80-92.
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From a Critical Discourse Analysis perspective, van Dijk (2015) refers to contextual models as evidence of the interface between the knowledge (mental information) about an event and its significance in the discourse. Thus, the remembrance expressed about a "biographical event" is also a signification of episodic memory. Can we state that contextual models evidence the meaning of memory in discourse?
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episodic memory associations can be encoded and retrieved in a context-sensitive way; thus it can be evidenced.
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hello ..
thank you for reading my quistion and i will appreciate any help. i am doing my master dissertation now which i am investigating gender represenatation in textbooks. my method is content analysis and i will collect data which includes genders of poets, scientists, authours, leaders and so on. i also will look at the appearance of each genders in varied areas. the data will be gathered from texts and pictures and i will interpret it (after analising) in charts and diagrams.
my quistion is does this process considered as qualitative or quantitave or mixed methods? and about the data is it qualitative data or quantitative ?
thank you
Fatema
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Mixed methods requires two sets of results, one qualitative and one quantitative, as well as the integration of the those sets of results. A straightforward content analysis such as you propose would not meet this definition.
Instead, it sounds like you want to do a quantitative content analysis (i.e., based on counting things), but you want this analysis to be essentially descriptive (i.e., you will not be testing any hypotheses).
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I am an international student and I am studying sociology at McGill University.
I am interested in the sociology of immigration (in particular, immigration in Canada) and have read research papers about this topic. However, I feel I'm stuck generating possible research topics for my final Master's research paper (it will be 30 to 40 pages long).
Does anyone have any exciting immigration study subjects in Canada for a Master's research paper? I am looking for both qualitative and quantitative research topics.
I also would appreciate it if you could introduce any interesting papers about immigration, mainly, in Canada
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(PDF) Immigration: analysis, trends and outlook on the global research activity (researchgate.net)
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Hello everyone,
How can I conduct a correlation test between two nominal variable gender and shelter type (5 categories) and other scale variable for example income, travel time, and shelter distance?
My objective is to show the significant correlation among variables.
Thank you.
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Look for eta coefficient
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Hello,
What do you consider to be the best methodological handbooks (covering both quali & quanti) for beginning researchers in the humanities and social sciences?
The views of doctoral students are particularly welcome :)
Many thanks in advance for your help!
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Isabelle Skakni A good rule of thumb to follow when selecting whether to employ qualitative or quantitative data is: quantitative analysis is preferable if you want to confirm or test something (a theory or hypothesis) and If you want to understand anything, use qualitative research (concepts, thoughts, experiences)
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Would you please share your kind opinion regarding this issue?
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You can calculate the mean of any set of numbers. e.g., 1,2,3, (1+2+3)/3 = 2. Being non-normal is different than wanting to estimate a parameter. If you mean something different please specify this.
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I am in search of methods of quantitative and qualitative estimation of cellulase in a food sample(biological sample)?
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  • Mendeley.
  • ReadCube Papers.
  • EndNote.
  • EasyBib.com.
  • Zotero.
  • Cite This For Me (formerly RefME)
  • Paperpile.
  • Sciwheel.
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My friend and I have arguments about some statistical assumptions. He thinks that if he has 4 constructs, and every construct has 3 variables, for example. To test a mediation analysis, he can take the mean average of these variables, compute it, name the average means, and start the mediation test. My argument is that he has to obtain the latent variable through load factors and make a path structural equation model. is both methodologies right? which is better?
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The resolution to your argument is an empirical issue. If there is relatively little variation in then loadings, then adding them will be adequate because it assigns equal weights to each variable.
FYI equal weights is the assumption with coefficient alpha, so a high alpha (say .80 and above) would suggest that simply add the variables would be adequate. Also, averaging simply divides by a constant, so it just makes the results more interpretable.
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I made the question to check people knowledge and how much aware they are actually of the terms, so I put only two correct questions and the rest is wrong but now I got 200 responses and many responses selected all, some selected wrong and write both(eg: one Right and one wrong). so I have no idea how to analyze. please help
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Hello Nelly,
Unfortunately, hindsight is so much clearer than foresight more often that we would like!
Unless you want to restructure the survey and collect more data, here's one option you could try:
Create an ersatz score, which could range from 0-8 for each respondent. If a respondent does not check an incorrect response option, you award 1 point. If a respondent does check a correct response option, you award 1 point. A "perfect" score of 8 would accrue for someone who checked only the two correct options.
If that's too complex, then simplify the above plan so that only perfect scores are given credit (perhaps, "1") and all others are given no credit (e.g., "0").
Good luck with your work.
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I think we make a mistake when we consider that data are qualitative if they come from applying qualitative methods and techniques or if they are collected in qualitative researches. I think we make the same mistake when we consider quantitative all data collected through, for example, questionnaires.
I think we have to consider the qualitative or quantitative character of data looking exclusively at data. Are they numeric? Are they textual or visual?
I think (as Traian Rotariu argues) that quantitative data are numeric and that qualitative data are textual or visual and that we could gather quantitative and qualitative data with each and every method and technique being it qualitative or quantitative.
For example most of the data gathered with questionnaires are qualitative in their primary form: opinions, gender, preferences etc. and just a few are quantitative in their primary form: income, age, children's number etc.
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To answer this valuable question, let me repeat what I have written in my recording sheet during my bachelor study:
  • While Quantitative data collection methods use mathematical calculations to produce numbers, Qualitative data collection methods concern with words and produce descriptions.
  • While Quantitative methods are more structured and allow for aggregation and generalization, Qualitative methods are more open and provide for depth and richness.
  • Quantitative and qualitative each has their strengths and weaknesses. Sometimes numbers are more useful; other times, narrative (qualitative data) are more useful. Oftentimes, a mix of quantitative and qualitative data provides the most useful information.
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I often read research articles that do not appropriate describe the sampling procedure. For example, the authors mention that the sampling was accidental or purposive but they don’t explain why they had only 10 participants or they say that the sampling was theoretical and describe the a priori established socio-demographic characteristics of their subjects.
I think that the sampling procedure is one of the most important elements of a research. I think that the research should be evaluated according to this procedure and I think that many pieces of research should be rejected because of sampling not being appropriate.
Please help me to clarify this and correct me if I am wrong:
The sampling procedure should state the sampling criteria and should justify the number of participants.
There are two kinds of sampling in social research: statistical – probability or non-probability (when the sampling criteria and the number of participants are established before entering the field according to some rigid sampling rules) and theoretical (when the sampling criteria and the number of participants are flexible, decided in the research process according to relevancy and saturation rules).
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Very useful discussion. I remember, the saying "it is better to study one rat for 1000 hrs rather than studying 1000 rats for one hr if you need to study behaviors of rats". But that particular rat should be selected carefully; not to choose a 'mad' or 'disabled' rat. Now by studying this carefully selected rat (theoretical sampling) we can generalize certain behavioral patterns of rats, as well as can gain a deep understanding of the behavior of rats, in that time and space. Observing 1000 rats, randomly or even purposively (statistical sampling), for one hour would help to identify a single or couple of features of rats, in that particular context. So, the sampling technique depends on the nature (not the purpose) of the research.
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Hello all
One of the most important tasks of a team leader is to define precisely the "priority" of goals.
We need a "questionnaire"? Related previous studies? To measure the priority goals of a team leader.
Thanks for your time.
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Nice question
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In the realist methodology (especially by Raymond Pawson et al), the CMOc is a common structure to explain what works, for whom, in what circumstances, and why?
I'm always asked about the criteria that the context and mechanism and outcome are indeed logically linked to form the CMOc? How ensure that there are causal connections between these components? What are your experiences on this? Any suggestions? Thank you.
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Great discussion
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I'm wondering if anyone can help me? I'm new to this subject and I'm finding it easy to find research regarding white researchers conducting research in 'ethnic minority' communities, but I'm struggling to find research regarding a black researcher conducting research in predominantly white communities.
I'm wanting to know anyone can point me in the right direction regarding research specifically detailing the impact of race with regards to a black researcher conducting research amongst predominantly white participants in a working-class area (that is predominantly white)?
I'm interested in research that has been conducted in the UK though I'm also open to research conducted in other countries.
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You might check with Dr. Shirley Wells at the University of Texas Rio Grande Valley.
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Data collection is an important step when doing any research or experiment. Data collection can be defined as the process of gathering and processing the information to evaluate the outcomes and use them for the researches. But with the development in methods of collecting data by artificial intelligence , do methods evolve in collecting data for social media.
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Dear Roberto - Minadeo Can you provide me with artificial intelligence techniques to collect data?
Regards
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I have a quantitative dataset that exists of 22 completed answers from a base of 72 respondents. The reason it is this small is because i am questioning why a specific market research bureau experience some "no's" from companies that contacted that market research bureau.
I know that of course companies say no sometimes, but i am looking into why they did this. Also my base only exists of potential clients from 2020 from Denmark, so that is why the base is 72. I would say that the completed answers would still be able to give some insights for the specific Market research bureau, at least for their 2020 clients base.
My Question is about correct analysis of these 22 completed answers; How do i properly handle the answers in descriptive and statistical analysis? There is many tests that are about the validity but those tests makes no sense on a 22 completed basis. I have thought about binary logistic regression in SPSS and maybe some crosstabs and Chi2 but i am afraid of missing out some way to make the best out of the small dataset. Maybe you guys have experience with this?
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Based on your question you may want to employ a mega-trend-diffusion technique (to estimate smalll data sets) to produce artificial samples .The tool used is the Pythia software.
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My main goal is to determine the ethical dilemmas and moral distress experienced by nurses during the pandemic and how does that experiences affect their performance at work.
So, Do I need to follow the theoretical framework of Kohlberg? if yes, how?
Or Is it okay to use the theory of kohlberg AS A GUIDE to help explain the nurses level of moral reasoning that made them perceived the situation as an ethical dilemma or a moral distress.
Thank you. I really appreciate the help and the clarifications.
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I agree with the sentiment that a good theory guiding the study is best, everything else being equal (e.g., good measures, adequately powered study) but I would also consider going beyond a goal of theory testing by considering a few other directions:
1) Examining two competing theories to see which one is more predictive.
2) Extending a theory by "adding" or altering an existing construct.
Of course the above should be based on good reasons, logic, empirical work, etc, if possible.
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I am currently planning a research project/Masters dissertation about women perpetrators of the Holocaust, and I am intrested in doing some primary research. I would like to access photographs of SS women and nurses in particular. I would like to explore these frontline perpetrators' dual role as 'ordinary' German women and merciless killers.
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There are nowadays digital sources in most of the European archives, including for the II World War. For Germany consult https://www.bundesarchiv.de/EN/ Navigation/ Use/Using-specific-types/Military-Records/military-records-en.html
For The Netherlands, you can access The Netherlands Institute for War Documentation at http://www.niod.nl/
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Can quality be quantified, if yes, how; if no, why?
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I agree with Raouf Jaziri
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Dear all
I would like to consider multiculturalism as an independent variable in a multivariate regression to figure out it’s effect on quality of learning in a big city. Can you advise a good measure way for multiculturalism?
Thanks in advance
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This article is one of the best things to read about: Planning in the multicultural city: Celebrating diversity or reinforcing difference?
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Students/participants who always use measurement or numbers in understanding all phenomena may require more effort in convincing them about the importance and processes of qualitative research.
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Hi.
I use several methods. Here are some:
1. I expose them to research questions that cannot be answered adequately by using qualitative tools (e.g., What is the experience of...? What does the process entail? How do the participants understand phenomenon X?, etc.). I also have them find a qualitative tool (i.e., questionnaire) that they favor, and demonstrate the areas that it does not cover (i.e., the richness of the experience under investigation).
2. Early on, I expose them to the different paradigms and their logic (I have them experience social construction and subjective meanings via an exercise wherein I show identical stimuli to two students but construct their meaning differently).
3. Early on I teach them the hermeneutic circle, and have them experience the cyclic process of understanding and re-understanding. I also demonstrate in various how parts and whole give meaning to each other (e.g., how the word "positive" changes it's meaning in "Are you positive" and "O positive" and "positive symptoms" and five other examples).
4. I also let them ponder several quotations that challenge their views (e.g., Nietszsche, Rorty, Geertz). For instance: "When we aggregate people, treating diversity as error variance, in search of what is common to all, we often learn about what is true of no one in particular" (Josselson, 1995, p. 32 "imagining the real")
Good luck.
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My 5-Likert scale is: (1= strongly disagree, 2= disagree, 3= neutral, 4= agree, and 5= strongly agree)
So: 1 & 2 become category 1, and 3,4,5 become category 2
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@Margarate Nzala Munakampe and @Ernest Owusu. This information may be irrelevant to you now but I felt I should still post it in case there is someone out there who may need it. Like you, I had to search for an article to support this dichotomization because in my Ph.D. research proposal I needed to convert my 5-point Likert scale data to binary for the purpose of analysis and I had to support that action with the relevant citation. I found the reference below very relevant:
Jeong, H.J. & Lee, W.C. (2016). The level of collapse we are allowed: comparison of different response scales in safety attitudes questionnaire. Biom Biostat Int J. 4(4):128-134. doi: 10.15406/bbij.2016.04.00100
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I am currently working on a systematic review and I am in the quality assessment phase. I am writing this inquiring about the quality assessment tool that I can use to assess non-randomized studies (mainly cohort study and cross-sectional study). 
Thank you so much and I highly appreciate your response in advance . 
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Thank you all. I made up my mind and we are using the NIH quality assessment tools.
Thanks
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How to measure "Quality tools in Higher education" .?
please suggest some methodology part for this
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It depends on the field of study and the specificity of the study's issues. Other quality research tools in higher education will be key in the fields of artistic studies, different for business, different for polytechnics, different for natural sciences, humanities, etc. Each study, taking into account the specificity of problems, issues, specializations, and improved skills, differ significantly. The only thing that can combine is the achievements of graduates in their professional work, in which graduates use the knowledge and skills they use to study. But this issue can often not be a universal measure of the quality of education if a significant part of graduates after graduation do not work in their learned professions, professions and specialties, but only undertake work completely unrelated to the completed field of study, even when they have completed a given field of study with good results. this is the case in some countries.
Regards
Dariusz Prokopowicz
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Hello
I have the following situation: I have a paper X about topic Y. For paper X I did a forward search with Web of Science (checking all new papers which cite paper X). Then I have downloaded all articles I have identified via forward search (approx. 1'000 Papers). Now I would like to sort these papers according to the frequency of specific keywords used.
For example: I have found paper Z via forward search (so paper Z cites paper X which is about topic Y). Now I want to check if paper Z is also concerned about topic Y or if it just refers to it in passing. For that I search for specific keywords which correspond to topic Y. According to the frequency of the specific keywords mentioned in paper X, I want to classify it in the category "relevant" or "not relevant". Now, how can I determine the threshold for the keywords? That is, if paper X only uses the specific keyword once it is most probably not relevant to topic Y. But if it mentions the specific keyword 20 times it is probably relevant for topic Y.
Is there a recognized methodology to determine or approximate a threshold for the keyword frequency which allows to distinguish if a paper is relevant to topic Y or not?
With this approach I hope to reduce the 1'000 papers to those which are about topic Y.
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I am currently working on a project which require me to use sequential explanatory research design. I have two groups of learners, A (treatment group) and B (Control group). I plan two have two parts of sequential explanatory research design.
Research Part 1 (Research Part 1 is without intervention for A & B)
Quantitative (Pretest Posttest) -----> Qualitative ----> ( Integration of Quantitative + Qualitative)
Research Part 2 (Research Part 2, A-intervention, B-without intervention)
Quantitative (Pretest Posttest) -----> Qualitative ----> ( Integration of Quantitative + Qualitative)
Thank you.
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Good information David
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Hello
I am working on the following: I have 65 exsiting definitions about a concept. From these 65 definition I try to distill a representative definition via coding procedures. Thus, I code each definition to find patterns.
Now I have all definitions coded. And I can see how many times a code is used in the exsisting definitions. For example: code X is present in 20 of the 65 definitions.
As I now want to develop a representative definition (and not one which contain all codes) I would set a cut-off-level. A cut-off-level in the sense of: only codes which are more then e.g. 20 times present in the exsiting definitions will be included in my representative definition.
Now I was wondering, is there a way to determine the cut-off-level statistically?
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I might ask: do you believe in qualitative at all? I think that "determining cut-off level statistically" is about quantitative... You should find out what "representative" means in qualitative sense. In short "representative" can be defined in terms of conceptual variation found in the data. I think that 65 definitions should be reduced towards few information intense ones, kind of conceptual cores.
The article "Analysing qualitative data" (2000) by Catherine Pope, Sue Ziebland,Nicholas Mays could be an informative source. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1117368/
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I am in my Third Year (Junior Year) of my undergraduate degree of Management Science in LUMS , Pakistan. I am new on Research gate, and I want to peruse my career in academics and research in area of Business analytics, in fact I have done some projects and experimental findings in this area. That Online affiliation which can be helpful for me for getting admission in Grad School in couple of years. I need suggestions of experts in this area of interest.
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Respected Roy Sir, thanks for your appreciation and your words.
Sure I am really happy to see your answer to my question and I am very enthusiastic for starting work with you.
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I am conducting a research to investigate the ergonomic risk factors among workers in a manufacturing company. I want to know if it is enough to have a sample size below 20 respondents? Is there any minimum or maximum criteria for mix: qualitative & quantitative method research?
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According to Creswell, W. & Creswell, D. (2018), the case study includes five to six cases.
Reference:
Creswell, W. J., & Creswell, D. J (2018). Research design: Qualitative, quantitative, and mixed methods approach. Sage publications.
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Hello! I am looking for assistance with a quantitative textual analysis. Below, I've created an small sample of what our current data (conversation between two participants) looks like.
Partner A:
Hello how are you?
Partner B:
Hey, Im good thank hbu?
Partner A:
Im good, What year are you in?
Partner B:
Im in forth year.
Ideally, we are looking for a line of code or a software that could take these log files and split them into two separate word documents or text files, with all of Partner A's comments in one file and all of Partner B's comments in another. Currently, we are manually splitting files, by copying and pasting them into the separated word documents, however, this is time consuming.
Additional Info: The two separated files of each conversation we have collected will be processed through Linguistic Inquiry Word Count (LIWC).
Thank you in advance.
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Personally, I would do this sort of thing in Python 3, which is free, high-level, has a number of nice distributions with built-in IDEs, and is pretty quick to learn. I just spent a few minutes looking over your example, and I think I produced the behavior you desire with the following code:
infile = open('*the file path containing your source text*', 'r')
outfile_partner_a = open('*the path where you want partner a's output text*', 'w')
outfile_partner_b = open('the path where you want partner b's output text*', 'w')
current_outfile = outfile_partner_a
for aline in infile:
if aline == ('Partner A:' + '\n'):
current_outfile = outfile_partner_a
elif aline == ('Partner B:' + '\n'):
current_outfile = outfile_partner_b
else:
current_outfile.write(aline)
infile.close()
outfile_partner_a.close()
When this is executed, the output text file for Partner A is:
Hello how are you?
Im good, What year are you in?
And the output text file for Partner B is:
Hey, Im good thank hbu?
Im in forth year.
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My research topic is related to cultural tourism in a known and unknown heritage centers. The already known heritage sites are known and there are also unknown. I will use both qualitative and quantitative research approach where the qualitative one will be mainly use FGD, Participant observation, case study and interview (mainly to respondents around the sites and institution). For the quantitative approach both domestic and international tourists will be the target population. However, they are unknown. Which formula is helpful for this type of study?
I will appreciate if you also drop me your ideas to hagosg@gmail.com
Thank you!!
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I totally agree with David, I think he has nailed it for you. For such a research topic you may want to look into "cluster sampling" to help you collect responses.
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Let say if I would like to study the (regression) relationship between Corporate Governance and Cost of Debt.
WHAT quantitative software should I employ to test it and WHY should I use the suggested software as I heard about SPSS, Smart-PLS and EView?
Thanks for advice in advance.
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Four programs you can use in your project EView, R, spss and Stata
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Opinions on the differences between qualitative and quantitative research approaches?
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There is a very large literature on this topic, under the heading of Mixed Methods Research. I suggest you read one of the several textbooks in that field, such as the one by Creswell and Plano-Clark.
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I am doing a risk management study while collecting both quantitative data and qualitative data via one instrument-interview. This one interview instrument contains qualitative data analysing from content analysis and quantitative data by asking participants to assess risk directly. As risk management includes risk assessment and proposing risk mitigation strategies, qualitative data intends to answer research question related to risk mitigation strategies, while quantitative data aims to solve research question regarding to risk assessment.
The problem is that I am confused about whether this instrument should be regarded as convergent mixed methods or embedded mixed method.
With only one instrument, can it be treated as convergent mixed methods?
Or if this is an embedded mixed method, neither the quantitative data nor the qualitative data can be regarded as supplement data to the other. In the other way, it is difficult to say one research question is more important than the other as qualitative data and quantitative data aims to solve different research questions. As they are of equal importance, this research method does not seem that it belongs to embedded mixed method.
Does anyone know this kind of risk management with one instrument is suitable to which kind of mixed methods?
Looking forward to your kindly answers.
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Embedded almost always means a larger quantitative study (such as a program trial or evaluation) that contains a qualitative component within it. Convergent studies require that both methods study the same thing to determine the extent to which the results agree (converge).
Since your study does not fit either of those criteria, it might be complementary, in the sense that each component of the project targets a different priority within an overall division of labor. Whether or not this fits depends on the extent to which the results from the two methods are connected to each other.
This raises the question of whether you expect the open-ended remarks to address the choice of the quantitative response? In other words, will the qualitative component help you understand the results from the quantitative component?
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I will use quantitative and qualitative research simultaneously to design a research in which I give equal importance to both. How should I determine the sample size? How many people? For example, in a quantitative study with 350 people, with whom of 350 people at the same time? according to what? v should I do qualitative work with other people?
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Hi David L Morgan you always have such good knowledge to share.
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Is it right or ideal to use only research questions in a triangulation method - i.e. qualitative and quantitative research?
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Triangulation generally means trying to answer the same research question with two different methods, but note that the editors of the Journal of Mixed Methods Research have now requested that authors no longer use the term triangulation, because it has too many different meanings.
Can you say more about the purpose that each of your methods will serve, and how they will be related to each other?
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Currently, I am writing a research on the impact of the interaction between information systems and Knowledge management on improving quality . Can anyone help me with a questionnaire, model or whatever. Thanks in advance.
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you should go to google scholar and type the topic.You will get a mix of papers both qualitative and quantitiave on this topic.Read the papers which show a pdf as they are free.
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In my questionnaire:
I have asked, " How frequently a certain topic is taught?"
A 4 point Likert scale was developed for the response where following values were assigned to each response:
Never: 1, Rarely :2, Often: 3, Always :4
Recently I have been told that for Never one should assign the value 0, as it's value should not be reflected in the final result.
To what extent it is correct.
P.S: With Value 1 to Never, my results look more logical than value 0
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Manisha - 4-point Likert scale is same as 5-point & 7-point i.e. each point have its own definition / label. The only difference is that in a 4-point Likert scale respondents don't have a choice to select neutral option. You need a range of numerical  values which could range from 1-4 and to to determine the minimum and the maximum length of the 4-point Likert type scale, the range is calculated by (4 − 1 = 3) then divided by four as it is the greatest value of the scale (3 ÷ 4 = 0.75). This range gives the weight of the responses. For example, if the total respondents is 50 and the scale range is 1= Never, 2= Rarely, 3= Often, and 4= Always. From your data set you ca calculate the responses. For further information, please see the following link on research gate:
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I'm new to conducting research and was wondering if anybody could enlighten me on what methodology would best suit my topic.
My thesis is about The influence of public outrage on media coverage of rape cases in Morocco.
On the one hand, I would like to analyze the impact of public outrage on social media, and on the other hand, analyze the impact of public outrage on the press (I've narrowed my sample to two newspapers).
Subsequently, I intended on comparing both points.
I've thought of a quantitative methodology with a correlational approach or a causal-comparative approach. However, statistics regarding any focal point of my research are non-existent.
Therefore, I decided to adopt a qualitative methodology instead, using a simple case study while trying to reformulate my hypothesis since it does not require statistics.
Any advice will be immensely appreciated.
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Hi Hayley,
You will first need to decide how you will measure 'influence' - and 'outrage'.
You can do this both qualitatively and quantitatively.
If you can specify parameters for influence (e.g. a higher proportion of articles) with outrage (was there a protest at the time? Or some measure of public outrage) - then you could see if the two measure correlate.
A qualitative analysis would definitely be useful.
Again - how you define your constructs will determine how you measure this - and you can then build a rich case study around this :)
I hope this helps.
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So I do both quant and qual research, but am rarely asked during a R&R to 'show my work' for quant pieces. However, almost all qualitative pieces that I receive a R&R have at least one reviewer who insists on frequency counts or quantitative evidence that my coding is legit. For this question please state your field, what you were asked to provide, and how the suggestion was clearly a misunderstanding of how qual research functions in your field.
I can't wait to hear your responses!
Yours in qualitative frustration,
Andrea
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I think the most maddening review was a couple years ago when I submitted a qualitative manuscript to a top tier journal in my field. One reviewer in the recommendations TOLD me to remove the word "empirical" when referring to our findings. Her/his position was that since it was qualitative it could not be considered empirical!
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I am about setting up a research design for my PhD thesis. The main topic will be sustainability innovation in companies. For the empirical research part I will use a data set consisting of corporate sustainabiliy publications such as annual reports, csr reports etc. and do a content analysis.
I am still a bit uncertain wether this qualifies as qualitative content/data analysis or quantitative content/data analysis. I would appreciate your feedback on the following questions:
- Would you classify the corporate sustainability publications as qualitative or quantitative data sources?
- Does software such as Maxqda, Atlas.ti or NVivo support a quantitative concent analysis as well?
Thanks for your input.
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Hi Erika,
It's down to the research question really - which I would be much more concerned about than which method to use. Think about the relevancy and contribution.
Sustainability being a rather complex phenomenon it is particular interesting to see how this is represented in company communications. I would think that you would have much more of a contribution in a more grounded approach.
Counting does not reveal much of a finding on its own - you can combine no problem, but essentially you may find something very interesting in codes that are not the most frequent. For instance, since companies tend to copy each other - new practices yet to be copied would not stand out in a count. What is more, sustainability reporting is also much about compliance - with this in mind I owuld posit that the 'outliers' could reveal very interesting findings.
Just some thoughts.
BR, Mai Linneberg
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"The difficulty of measuring attitudes, character, and personality traits lies in the procedure for transferring these qualities into a quantitative measure for data analysis purposes."
"The recent popularity of qualitative research techniques has relieved some of the burden associated with the dilemma; however, many social scientists still rely on quantitative measures of attitudes, character, and personality traits."
How do I know the effective kinds of research techniques(qualitative or quantitative) to analyze Likert item questions?
Any Help is Appreciated
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First, I am not clear what you mean by the "qualitative" interpretation of items with Likert scores. Most people interpret qualitative as coming for open-ended rather than closed-ended questions.
Second, there is a major difference between separate Likert-scored items and scales that you create by combining such multiple items. Because there have been so many questions here about creating scales from Likert-scored items, I have collected a set of resources on this issue:
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Hello,
I am trying to run tests on SPSS for an dependent variable which is a an interval and independent variable which is nominal. Can anyone give me some suggestions and how to do it?
Thanks.
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Hi, James,
The most obvious test is a univariate ANOVA which will allow you to compare the nominal categories to identify group differences on the dependent variable. If there are only two categories for the variable measured on an nominal scale, you could also use a t-test. If you are interested in the correlation between the two variable you described, you should run point biserial.
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Dear friends and researchers,
I just started my PhD journey as a new phd student, so I am preparing my proposal doc, My phd thesis in communication studies, specifically in health communication. I will investigate the role of mediated communication such as Twitter or Facebook in public health issues. I will focus on immunizations. Anti-vaccination groups make some campaigns and post many messages and posts about the risk of vaccines through social media, while the health authorities attempt to fight these movements and educate people about the importance of vaccination. I will examine the impact of public health messages of childhood vaccination on parental attitudes toward vaccinating their child. The mediated communications which address a common health concern among parents will be the focus, and I will apply my study to two different countries: Saudi Arabia and Australia.
My Question that I need your help with is: Do you think its better to do that through using Quantitative or Qualitative method by choosing a case study such as "Measles Vaccine issue" as a case study in both KSA & AUS, and use two 2 tools to collect our data (questionnaire+interview) Or (content analysis+text analysis) or (questionnaire+content analysis) that' may help to manage the research later, rather than using mixed method that needs to build questionnaires and survey for both country, which needs harder effort?
Best Regards,
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Trying to do a questionnaire would require recruiting over 100 responses in each of the two countries, so that is a major consideration. As an alternative, I would suggest using a coding system to make systematic comparisons between the two countries, and then following that up with either qualitative interviews, or in-depth examination of the original texts.
In mixed methods research, using follow-up qualitative interviews to understand the results of a quantitative content analysis is known a "sequential explanatory" design. Alternatively, you could follow-up the quantitative content analysis by returning to the original texts to generate a qualitative account of how any who the results came out the way they did. Here is a link to an article of mine that describes the second option:
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Most of the people think that purposive sampling is only applicable for qualitative research !!! Please share your opinions....
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All respondents are chosen based on a specific purpose, objective and question to fulfill the research demand. So, whatever, it is qualitative and quantitative, we can use the purposeful sampling for both qualitative and quantitative research as there is no barrier.
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Hi All.
I am conducting a study on occupational stress management. I have been advised to use Interpretative Phenomenological Analysis to do this but I have mixed feelings about it. While IPA explores respondents' lived experiences and they way make sense of phenomena, is it still a suitable method to analyse people's occupational stresses and their coping mechanisms?
Thanks,
Marta
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I do agree the view of an opportunity for an exploration of your topic by means of IPA. Here, Hetherington’s study/methodological consideration may be helpful, namely: …..the study uses interpretative phenomenological analysis to gain insight into the experience of occupational stress amongst a sample of signed language interpreters in the North West of England. The findings suggest two significant causes of occupational stress for signed language interpreters…..Interpretative Phenomenological Analysis.....is to gain an understanding of psychological processes/individual perception/experience in relation to occupational stress….(see: Hetherington, 2011, pp. 9, 138 and 141).
  • Hetherington, A. (2011) A Magical Profession? Causes and Management of Occupational Stress in the Signed Language Interpreting Profession, in Leeson, L., Wurm, S. and Vermeerbergen, M. (eds.) Signed Language Interpreting: Preparation, Practice and Performance. Manchester, UK: St. Jerome Publishing, pp. 8-9, 138-159.
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Mixed methods research is a methodology for conducting research that involves collecting, analysing and integrating quantitative and qualitative research.
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Mixed methods research can have many advantages when the design being used is well chosen to meet the goals of the research question. At the same time, however, it can be quite challenging not only to use more than one method but also to integrate the results from two or more methods. So, I recommend starting by evaluating the extent to which the "best" single method could accomplish your goals, and then ask what you could gain by adding an additional method.
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I think that I belong to qualitative paradigm. However, I can’t deny the attractiveness of quantitative approach in terms of labour effectiveness and the number of participants I can collect data from (through an online survey, for example). Research methods books often mention the incompatibility of quantitative and qualitative research like ‘water and petrol’ in terms of research philosophy. Are they really ‘water and petrol’?
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I agree with others that qualitative and quantitative are not paradigms, they are applied approaches research to research design and methods. I disagree, however, that you need to look more deeply into abstract issues of philosophy. Instead, I would advocate looking into mixed methods and the typically ways that combines qualitative and quantitative methods.
In particular, you should think about your purposes for using each method, as well as how you would effectively integrate the two sets of results.
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Can anyone suggest me tools or a model to apply in doing a linguistic critical discourse analysis of newspapers?
Thank you very much indeed.
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Dear Jamal,
You have to have a good command of Systemic Functional Grammar by M. Halliday. The common denominator of Fairclough, van Dijk , Hodge and Kress and van Leeuwen is their employment of Systemic Functional Grammar. If you would like to focus on "who did what to whom, what is not said rather than what is said" concerning social power abuse, dominance and inequality, read Halliday.
Best,
N. Kansu-Yetkiner
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Their particular difference in terms of GMP.
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Agree with @ Roman Aleksander Tabisz. regards
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I am working on a project in which I have to use different psychometric scale (Pro environment behavior) items developed and validated by different authors.
As I know, this process is called adapting , which is different from adopting or developing a scale. And also, I have to again perform the reliability and validity test.
I want to ask that what are other procedures which I have to follow.
What are the things which I have to do after preparing the questionnaire and pilot survey.
Can you suggest me some readings on this topic so that I have some theoretical understanding of the process?
Thanking You,
Pawan Kumar
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Dear Kenneth,
please note that there is a large literature on how to avoid exactly that (comparing apples and oranges). If he develops a new scale there is no way to connect his research with the research already conducted in other cultures wrt. to the construct in question. You are right, that this runs the danger of comparing apples and oranges, but as I said this can be avoided:
Spini, D. (2003). Measurement equivalence of 10 value types from the Schwartz value survey across 21 countries. Journal of Cross-Cultural Psychology, 34(1), 3-23.
Schaffer, B. S., & Riordan, C. M. (2003). A Review of cross-cultural methodologies for organizational research: A best-practices approach. Organizational Research Methods, 6, 169-215. doi:10.1177/1094428103251542
Stark, S., Chernyshenko, O. S., & Drasgow, F. (2006). Detecting differential item functioning with confirmatory factor analysis and item response theory: Toward a unified strategy. Journal of Applied Psychology, 91(6), 1292-1306.
Steenkamp, J.-B. E. M., & Baumgartner, H. (1998). Assessing measurement invariance in cross-national consumer research. Journal of Consumer Research, 25, 78-90.
Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4-69.
Best,
Holger
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Dear Colleagues/Friends,
I’m conducting and informal survey on multidisciplinary research. This stems from a keynote paper I delivered at the international conference on advanced multidisciplinary studies (ICAMR). If you have time, your input is extremely valuable and highly appreciated. The intention is to fix problems and provide a qualitative and quantitative summary of benefits, problems, recommendations and solutions.
The basic questions I pose:
1. Pros/Benefits/Advantages:
2. Cons/Detriments/Disadvantages:
3. Problems/Roadblocks:
4. Recommendations/Solutions:
5. Examples (should you have time):
Personally, I am a very strong advocate of team-based applied multidisciplinary research across hard (natural) sciences, soft (social) sciences, and humanities. I have been involved with a wide spectrum of international multidisciplinary projects for 30 years. I understand tradeoffs while insisting on fair stakeholder identification, engagement, inclusion, and benefits across the board. I firmly believe that’s the ultimate goal for most of us.
Despite lip service claiming to welcome and promote multidisciplinary research, I find many roadblocks remain unnecessarily common, counter-productive and sometimes insurmountable – especially between stove-piped disciplines and their administrations at multiple scales: for example, 1) among practitioners, 2) within institutions (private, public, government, academic, corporate, think tanks, universities, international organizations, NGOs, grass roots organizations, religious institutions, etc.), 3) among multiple institutions, and 4) among multiple countries and their institutions at the international scale. Some are expected and unavoidable. I get it. It’s part of the necessary aspects of the administrative process, etc. However, there must be solutions for many other common issues and ways that many processes can be streamlined. Again, the intention of this survey is to fix problems and provide a qualitative and quantitative study on the benefits and problems with a summary of recommendations and solutions.
Thank you in advance for your considerations and cooperation.
Yours sincerely and best regards,
DKL
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All involve a coming together of multiple disciplines to approach a problem but differ in whether knowledge is shared in a way that is additive (multidisciplinary), synthesized and harmonized (interdisciplinarity), or integrated and transcendent (transdisciplinarity) across disciplines (Alvargonzàlez, 2011; Choi & Pak, 2006).
Alvargonzalález, D. (2011). Multidisciplinarity, interdisciplinarity, transdisciplinarity, and the sciences. International Studies in the Philosophy of Science, 25(4), 387-403.
Choi, B. C.K., & Pak, A. W. P. (2006). Multidisciplinarity, interdisciplinarity and
transdisciplinarity in health research, services, education, and policy: 1 definitions,
objectives, and evidence of effectiveness. Clinical & Investigative Medicine, 29(6), 351-364.
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My study is based on skilled returnee to their home country and there are two types of them , one came home country with the job offered by government and other find job on their own after return to home country. Choice of coming back is ranked on the scale of 1-10 .
question that i need to find answer for my project is that
Do returnee with govt fellow and non fellow differ significantly on choice of reason of returning to home country ?
Should i use Mann-Whitney test or kruskal wallis test?
Thanks
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Hi Kanika,
The Mann Whitney U test is used to examine the difference between the two groups, while the Kruskal Wallis H test is used to examine the difference between more than two groups. So the selection of the Mann Whitney U test is correct.
Examine the distribution of the groups for the relevant dependent variable.
Nonparametric tests have less power than parametric tests.
Best, İbrahim.
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Hi all.. was wondering if anyone is aware of any online sources or books which gives an overview of social pharmacy methods. I am thinking of an overview of anything stretching from:
1) Which methods are available (quan or qual)
-2) How to determine which quality appraisal tools to use (dependent on methods)
3) Internal and external validity (again dependent on methods)
4) How to analyse findings (economic calculations, statistic etc)
// Sara
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This is a good book on Social Pharmacy. I learned Social Pharmacy from this book. https://www.crcpress.com/Social-and-Behavioral-Aspects-of-Pharmaceutical-Care/Wertheimer/p/book/9781560249528
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I have conducted a study and distributed a questionnaire to students and found that they are less motivated to study English.
I decided to do an interview asking the reason behind that from teachers' point of view.
so, How many interviewees are needed for my study?
Thank you!
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Please refer to the following links, where the valuable views and discussions/referred publications/suggested number of interview/data saturation, etc. should be helpful.
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I have conducted a quantitative and qualitative research for a research question, i.e. Challenges of KS & R within Oil & Gas sector of Pakistan. Results obtained from both the methods are complementing each other. What triangulation type is it referring to? And how can i justify & prove data triangulation? Please share any sample study for example? Thanks alot.
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Triangulating data will elucidate themes and improve the accuracy of the qualitative results. Triangulation involves multiple data sources collected through different methods in an effort to improve the validity of the qualitative results (Patton, 1999). Member checking could ALSO be employed to validate findings and resolve any potentially conflicting results (i.e., member checking is a qualitative method used to valid researchers findings with participants viewpoints). Marianne Storm any additional thoughts?
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Typically, researchers look for evidence of content validity, criterion-related validity and construct validity when assessing the validity of a study. If one uses existing scales from existing studies, do you still need to test for content validity? Other than getting judges, could content validity be conducted using SPSS or AMOS? If yes, how?
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hai Tze, may i know how u calculate the CVI? content validity index? using excel? or spss?
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Dear members,  
I have a set of ten statements about opinions of benefits of foreign education upon return to home country on scale of 1-5 ( strongly agree to strongly disagree) . It is not developed using Likert scale/ factor analysis method. Given that would my statements be ordinal in nature? And what would method to combine them together as one index of showing benefits of foreign education. And in second case , will the index can be  as scale measurement and use t- test.
Thanks in advance 
Best regards 
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You have a set of Likert-scored items, which could be combined into a scale.Because there have been so many questions here about that topic, I have created a set of resources at:
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How to determine the justification of sample size in Qualitative and Quantitative Research?
How can you know that the research sample size have been justified?
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Hi Mary,
Both paradigms require different justifications. For quantitative, newest technique is based on adequate power in order to produce statistical significance. There are quite a number of statistical calculator to determine the sample size such as:
2. G*Power
For qualitative, the number of participant ceased when the saturation occur. Although there are several sample size guidelines and it is presumed that more participants might provide more information, you should stop when the participant no longer providing new insights.
You might refer to
Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field Methods, 18(1), 59-82.
Hope this helps.
Aliff
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Which techniques do you reccomend for quantitative term mapping? We are conducting a literature review to disambiguate a group of closely related technical words in education. Or aim is to provide a clear definition for each of them, as based on the mainstream use among researchers in the field. We were thinking on a quantitative analysis which helped us conducting kind of a cluster analysis of the most often alluded meanings under each term. Can you reccomend something?
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So the first step would be to 'lock down' the terms / lexicalizations. You can do a bit of explorative reading to get to them, of course. But you should not just build up the totality of the corpus as you go. That will skew tha data to some direction. Don't try to go wide by getting many terms. Try to get deep by getting a few terms in as much different contexts as you could possibly lay your hands on. Typically you'd want your corpus to reflect the balance of contexts in the actual discourse. But, often enough, insights are gained by the odd low-count contex . So do try to get them in, even if at an expense of balance.
Then, 'lock down' corpus size. Corpora grow to be virtual behemoths these days (up to millions and tens of millions tokens). If you'd like to retain the option to close-read when necessary you'd want to go on the low end -or design for sub-corpora. Sub-corpora are extra nice, because they can allow for keyness analyses (texts where your terms are key would be more likely to elaborate on them). So, get your size fixed and go reach it, without changing your mind about what should go in and what shouldn't midway. Ideally, you'd want to crowd-source that part; it both speeds up the procedure and keeps you impartial. Set up a Train-Test split (dedicate part of your data to derive your scheme from and part to test it on). You can also go for a cross-testing arrangment.
Perform standard collocation and collostructional analyses with your terms as KWICs and wide enough spans on both sides on your Train set. See if any interesting n-grams -including skip-grams- with discriminative power pop-up (n-grams mostly showing up with one but not the other term). Run collocation analyses on items in them too. If an n-gram strongly selects a term as collocate both ways and not another, well done, you've found a disambiguating feature. Add the feature to a lexicon. You'd want at least one disambiguating feature for every term touple. Once there's a scheme in place, evaluate it against the Test set. Observe where it hits and where it misses. Go back and refine as necessary.
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My work is to explore the occupational choice of skilled returnees to India.whereby will associate there occupational choice upon return to age, educational qualification and type of visa held, with perception based questions about benefits of foreign education and work upon return to the home country. Should I include occupational choice of non-migrant ( those who have never been to abroad) in the analysis as well. if yes, how to analysis/ include non-migrant as control variable in my work?
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The role of control variables in a quantitative analysis pertains to spuriousness. If you have a regression model with just two variables, then you're likely to see higher effects. For example, if I examine the impact of education on income, then I may see a strong relationship--those who have higher education tend to have higher income. If I add control variables such as years of experience, then I will get a reduced effect size for the education variable. That's because years of experience also predicts income. Control variables are there to help account for potential spuriousness in your model since you cannot experimentally vary any of these variables.
To answer your other questions:
1. If you include occupation of choice, then you cannot do traditional regression analyses. You may want to make occupation of choice an outcome variable and try to predict it using a procedure called multinomial logistic regression. It basically checks to see which variables increase or decrease the odds of having a certain nominal outcome when compared to a reference category.
2. Your question about analyzing non-migrant as a control variable simply requires that you dummy code (code as zero for no or one for yes) whether or not the respondent qualifies for your definition of migrant. Include it in the analysis. You typically want the affirmative to be coded as one, but you can also base it on which is most common. For example, women are often coded as one in regression analyses in criminal justice research due to their reduced frequencies.
I hope this helped!
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