Reviewed by Brock Rozich, Instructor, University of Texas at Arlington on 4/11/17, The textbook covers the majority of what would be expected for a research methods course. I did not detect any issues with grammar, usage, etc. From what I can tell, the book is accurate in terms of what it covers. To me it has always just seemed like on more hoop to hop through. Instructors using the text for other domains, such as education research, will be interested in elaborating on concepts using examples specific to the needs of their students. In traditional statistical software, users were stuck with the pre-packaged noise distribution, and had no way to change it, so they transformed their data and squeezed them into the software. It is a timeless - if necessarily limited - resource, and be returned to again and again. Little is presented or discussed on electronic surveys, survey platforms, or the use of social media in recruitment, survey distribution or every survey completion. At that point, you can build a very simple (heterogeneous, not spatial) hierarchical model. There does not seem to be any culturally insensitive or offensive text. For example, a back to the Table of Contents (TOC) button would be nice, as well we a list of all subsections (hotlinked) added to a long version of the TOC. One of the books strengths is its focus on the foundation of research methods: the relationship between theory and observation, the understanding of science, and the logic that underlies the process of research. read more. Undergraduates will likely require supplemental materials and additional case studies to grasp some of the concepts covered. More examples would also be helpful. What Daniel Lakeland suggests sounds like the right thing to do for modeling credit and debt in a single variable. This is a minor omission and there are others one might quibble with. For example, Chapter 7 addresses scale reliability and validity. An index/glossary is not included with the text, but the table of content clearly outlines the topics discussed for each module. For example, in the quantitative analysis section, only a handful of basic analysis were discussed in detail (univariate analysis, hypothesis testing, t-test, regression). It presents an economic argument to the potential advantages of log-transformation of positive data. We consider these strong factors. But opting out of some of these cookies may affect your browsing experience. The relevancy and longevity of this book are great. For example, chapter 11. Examples were broad and not specific to an individual race or culture. The content is written in a way that will allow for longevity of use. The content does not read in a way that seems (either now or in the future) likely to read as dated or obsolete. You fill in the order form with your basic requirements for a paper: your academic level, paper type and format, the number This might be the most appealing point of the text for me. Chapter titles are hyperlinked within PDF copies to simplify navigation. As this textbook is designed as a succinct overview of research design and process, more practical topics are not included in much detail such as how to conduct different statistical analyses using SPSS or SAS, or how to interpret statistical analysis results. It would make a good alternative to more elaborate basic research methods textbooks when the instructor wishes to keep costs for the students low. I can understand not talking about instantaneous interest and calculus, but no logarithms? This is more challenging when planning for its use in an undergraduate research methods class; however, I think that the strengths of this book outweigh the weaknesses. In these kinds of models, the x[n] are called exposure terms. . as shown below. This text includes very few of either, so I think this text could be used for many years to come. Some areas for improvement would be to include historical scientific figures who are not all male, and link critical methodology in a clearer manner with specific critical and cultural examples of this form of research. In short: it's not a black-or-white discussion. I think I was, I think an important feature of this study (CARAMAL) is that the research question it was asking was doomed from, OK, fair enough. The chapter and subject headers all seem to be clear. This makes the book quite comprehensive in that the book could be used for the length of the semester, one chapter per week. Normality of ri is hardly guaranteed, but in practice there is often a good fit. Dr. Bhattacherjee's "Social Science Research: Principles, Methods, and Practices," is a comprehensive, but a bare-boned (and generic) introduction to social science research. Indeed, this is one of the strengths of the book: that it can be used broadly within the social sciences. (i.e., raw score =15, mean = 10, standard deviation = 4. However, both the breadth and depth of information might be too elementary for Ph.D. and graduate students. I later realized that they are not necessarily very long chapters; it varies in terms of the topic. The text is divided into 16 chapters, which corresponds seamlessly with a 16-week semester. This complicates their interpretation. The book includes some helpful figures illustrating concepts in research design and statistics. The chapter also does not present how the research design and threats to validity are interconnected. This book is designed to introduce doctoral and graduate students to the process of scientific research in the social sciences, business, education, public health, and related disciplines. In your methodology, you suggest to 'exclude cases pairwise' instead of listwise. This book is probably comprehensive enough for a 3-credit methods course with test-based assessments in a program where few students pursue graduate work. The discussion on research ethics is certainly a nice addition to the book where many other research methods texts lack. Chapters could be taught out of order and can be subdivided accordingly. So far, I have had commitments to translate thus book into Chinese, French, Indonesian, Korean, Portuguese, Spanish versions (which will hopefully be available in 2012), and I'm looking for qualified researchers or professors to translate it into Arabic, German, and other languages where there is sufficient demand for a research text. From a structural perspective, neither the chapters nor subsections are very long because Dr. Bhattacherjee writes concisely. Birthday: This, The "vaccine effectiveness" numbers used for approval were calculated based on preventing infection. However, I have an issues with the language in chapter 2 about about strong and weak hypotheses because it seems to treat the experimental/causal hypotheses preferentially. Students planning to conduct original research, analyze data and interpret results will likely find this insufficient. There are some cases when the author gives advice that I don't agree with (i.e. Quantitative Analysis: Inferential Statistics. 165.22.77.69 What it comes down to is this: publicly, To Daniel: "Watson and others like him want to provide a public service to the world by donating their time, Yuling: Yes, balancing doesn't make complete sense in the context of political polarization. One other argument I have heard in favor of not log-transforming reading time data is that log transforming can make an interaction non-significant, or make a non-significant interaction significant. The theories outlined here are the classic important debates, and the breadth of knowledge the author imparts is extremely comprehensive and up to date. The chapters for this book are organized into five sections: the introductory section, a section dealing with the basics of empirical research, sections on data collection and data analysis, and a final section that deals with ethics in research. my preference would probably be to impute small values as draws from some distribution, Id probably tend to use a gamma distribution, and try a few different sets of parameters. Maybe I am missing something obvious, but how do you justify using a given base in terms of interpretability? There are no extra navigation features (a link to take a reader to the table of contents in a header or footer, etc.). It is not comprehensive enough to be the only text students encounter, but it would be sufficient for say master's level programs that focus more on capstone or practical "informed by research" projects. It builds upon basic topics to more advanced concepts, so students from various backgrounds of research experience should still find the text useful. This book is based on my lecture materials developed over a decade of teaching the doctoral-level class on Research Methods at the University of South Florida. The textbooks is very accessible and easy to read for someone new to the disciplines of social science. Suppose you have areas n in 1:N with data y[n] for each area is population. I find it provides sufficient contextualization and examples for graduate students with some background already in research methods. Cross Tabulation Analysis Explained Therefore, HNCS can be considered as a holistic scale. However, many of the images were blurry (e.g., Figure 8.2, Table 14.1) and some fonts were smaller than others (i.e., pg. More examples and case studies, for example, could improve the text's thoroughness. A glossary would be helpful as students often need to reference basic definitions as they learn these new concepts. The random variable x is the number of males in the group who have a form of color blindness. While discussions are brief and concise, the text addresses the main issues and processes providing an overview and general understanding of the research process for social science You can model things on the log scale and then present results on the original or log scale as appropriate. That is, I'll explore the data (hence, exploratory factor analysis). This book is based on my lecture materials developed over a decade of teaching the doctoral-level class on Research Methods at the University of South Florida. Questionnaire Design and Surveys Sampling - UBalt in the text. There would be no problem dividing the chapters up for a class, or using a portion of the book. One area needing updating (or that instructors would need to supplement) is Chapter 9 on Survey Research. Now, if questions 1, 2 and 3 all measure numeric IQ, then the Pearson correlations among these items should be substantial: respondents with high numeric IQ will typically score high on all 3 questions and reversely. Occasionally, there were instances when the flow made sense at the chapter level, however, content might have been spread between chapters (i.e. I still think this is a good practical approach. However, the book falls short in the development of students' research skills. Two areas could be more in-depth, specifically the IRB discussion and the chapter on surveys. How to score a likert Scale Id recommend centering (just subtracting the means) rather than standardizing (subtracting mean and dividing by the standard deviation, i.e., z-scores). The information is presented in laymans terms without any jargon. Learning about methods is important, but not much is gained from that knowledge unless the student also learns how to execute at least some techniques. When dealing with any sort of economic or accounting data log transforms are absolutely necessary. A variety of data collection methods and concepts are discussed in an easy to understand manor. Important terms are also highlighted by bolding, making it easy for the reader to identify the important concepts. Prose is direct and to the point, giving only the essential information so as to allow the learner to develop a grasp of fundamentals. The final chapter, 16, covers Research Ethics, which seems to have been lopped on at the end of the text. There are useful definitions of key terms throughout the book, although none of the chapters go into much depth. It will have to be read in conjunction with discipline-specific guides to conducting research (and, most likely, alongside examples of good and bad research), but this does nothing to detract from the book's own value: it will certainly offer a valuable overview of key concepts, ideas, and problems in research design and data-collection, and will serve students throughout the duration of their studies and not just for one class. The purpose of this quantitative correlational research was to assess the extent to which preK-12th-grade (male and female) educators beliefs and knowledge regarding grade-level retention are related to their teaching experience, and grade level taught, at an international school located in the UAE, and whether the relationship patterns by gender were similar to the pattern for the Thats what I was initially taught about how to think about the normality assumption in my original field. Each module can be a standalone unit and is very adaptable to instructors who want to teach with either the whole book or individual modules. So let's now set our missing values and run some quick descriptive statistics with the syntax below. Quizlet There are useful definitions of key terms throughout the book, although none of the chapters go into much depth. You can use logs to make the model more useful and sensible without actually presenting results as logarithms. Get 247 customer support help when you place a homework help service order with us. Reviewed by Alysia Roehrig, Associate Professor , Florida State University on 11/5/18, This text provides an overview of many important issues for my graduate research methods course in education. However, various chapters could also be used alone or as supplement to other materials and excluding chapters not relevant to a particular course should not cause any issues. Lay people are sometimes uncomfortable with z-scores for a couple reasons. Generally the major topics are covered. Standardized Scores The text consistently matches the book outline. In other words, its a cesspool all the way up (sorry about thatthe metaphor decomposed when I changed direction). Not quite. I agree with another reviewer that the ethics portion seems like an appendix, rather than an essential and structural part of the book. Nominal However, it does so at a fairly superficial level. With everything that is (has been) happening in the U.S. and world, there are many examples that can come from the social sciences. Our custom writing service is a reliable solution on your academic journey that will always help you if your deadline is too tight. Factor analysis examines which underlying factors are measured, the software tries to find groups of variables, only 149 of our 388 respondents have zero missing values. For instance, I don't cover Chapters 14 and 15 in my own class, because we have dedicated classes on statistics to cover those materials and more. If your course is also covering descriptive inference, you would want to supplement the text with additional material. This cookie is set by GDPR Cookie Consent plugin. However, as I was reading through this book, I kept thinking that I would need to supplement multiple areas of this book with more information in order to make it truly accessible to my students. Again, this book can serve as an compact introduction in a graduate research methodology class for students across the social sciences, but it would work best in conjunction with deeper and more discipline specific materials prepared by the professor. For example, some topics for which the book provides helpful structure include i) Thinking Like a Researcher, ii) The Research Process, iii) Research Design, iv) and Sampling. CC BY-NC-SA, Reviewed by Cahit Kaya, ASSISTANT PROFESSOR, University of Texas Rio Grande Valley on 10/17/22, I LIKE THE FIGURE EXPLAINING RELIABILITY AND VALIDITY ON PAGE 55. Standard deviations away to the left, then one and two standard deviations to the left and so on. There are data-sets where 3 out of 547 data points drive the entire p<0.05 effect. Data can mean many things. More social Learn more here. . New terms are bolded with clear definition, and sometimes they are illustrated with examples. No problems with typeface, the diagrams and graphs are incredibly useful in breaking down more complex research methods. -how to search the literature The content is accurate and unbiased, which may be particularly important for texts on research design, as many fields within social science are intractably polarized between quantitative and qualitative approaches. Did that bottomless soup bowl experiment ever happen? This book is designed to introduce doctoral and graduate students to the process of scientific research in the social sciences, business, education, public health, and related disciplines. So if I try to summarize for myself, Daniel shows a clever way to scale the dependent data, while avoiding log(0) = -Inf values. The clarity of the text is sound partly due to the concision of the book. Each of the modules / chapters can also be used as subunits of a research method course without putting the reader at a disadvantage. The nice thing with this text is that you could rearrange as you see fit for your course without an issue. It's also a good idea to inspect Cronbachs alpha for each set of variables over which you'll compute a mean or a sum score. This book is a nice walk-through guide for researchers new to the field of social science research. Lay people are sometimes uncomfortable with z-scores for a couple reasons. Personally I would use whatever presentation or plot that makes the best case. we must understand that sometimes, these constructs are not real . Reviewed by Anika Leithner, Associate Professor, California Polytechnic State University on 7/15/14, This text certainly covers all the basic concepts and processes I would expect to find in an introduction to social sciences research. I found no errors in fact in the textbook. The author puts many words in bold type and then defines or describes the word. I also think Chapter 6 - Measurement of Construction should not come before Chapter 7 - Scale Reliability and Validity since measurement of constructs and scale reliability and validity are related to qualitative research. It's a great starting point for teaching my students to think about the basics of social science research and provides a nice skeleton on which I can layer more in-depth material for my course. In that sense, the book has very few opportunities to broach hot-button topics except when dealing with historical or ethical examples. It makes it sound like you have some strong assumption in place about how the log odds transforms your data into a line or something Theres nothing preventing you from doing nonlinear models though. But don't do this if it renders the (rotated) factor loading matrix less interpretable.if(typeof ez_ad_units != 'undefined'){ez_ad_units.push([[250,250],'spss_tutorials_com-leader-4','ezslot_11',120,'0','0'])};__ez_fad_position('div-gpt-ad-spss_tutorials_com-leader-4-0'); Thus far, we concluded that our 16 variables probably measure 4 underlying factors. You could also do it with more general ones. Although some instructors prefer to cover some chapters earlier (or later) in their semester/term than others, this is just a personal preference. Logarithms may be hard for some people to understand(*), but theyre required to get the model closer to the process that generated the data. Join LiveJournal Faculty would be able to easily divide the text into smaller sections, which would be useful as those smaller reading sections could be combined with targeted supplementary materials. In some instances, definitions are so concise that I find it necessary to elaborate with examples. The bolded words invite the reader to create a self-guided glossary, not any different than a textbook in an 8th grade student collection, which is helpful to counter the sometimes sophisticated nature of research theory. If there are any new or interesting content that you wish to see in future editions, please drop me a note, and I will try my best to accommodate them. We get 51 degrees when we do X minus two sigma. Not to mention that focusing on whether the effect is significant or not is utterly insane, but there Im preaching to the enlightened on this blog. I do really mean it!). Once could use this book as an entry to the field, but would need to seek additional resources for specific methods or analytical skills. The text provides a complete summary of the research process. I will be adopting this text to supplement other readings assigned in my master's-level research and analytic methods course. Likert Scale: Explored and Explained One thing that's lacking is a chapter on statistical graphics. The charts and images provided enhance the understanding of the text. The inclusion of some cases or examples showcasing how social science research methods can be applied to current events or topics would help illustrate the relevance of this book (and social science research). While the notes state it is intended for graduate coursework, I would have no problem teaching in my undergraduate courses. Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors. The text is well-written and provides clear yet concise context. It follows the conventions of including relevant key words and phrases in bold and includes easy to follow definitions of terms. > you can just go ahead and impute the negative values, zeros, and below detection limit values to something reasonable. For example, chapters 13 15 on statistics could easily be omitted if the program has a research statistics course. Dont do it mechanically or just to get a better fit. However, it would have to be supplemented heavily with other materials, as well as lectures, which is not without a trade-off cost. Professors will need to make sure that their slides include discussion of the degrees of freedom idea and perhaps some discussion on unbiasedness as well. Of course, most students seem to prefer an electronic text, so I assume they use a search function rather than an index. Analyze Likert Scale Data I use this book with graduate students in education taking an initial course in education research. For example, when discussing the tendency of lay people to view a scientific theory as mere speculation the author uses an example of teacher practice instead of a more charged example such as evolution. Learn more here. So if you have an assay that runs 17.31 oz/ton, you cut it to 1oz/ton. Research on the role of technology in teaching . Reviewed by Peter Harris, Assistant Professor, Colorado State University on 12/5/16, This is a comprehensive overview of research design and research methods in the social sciences. The authors prose is clear and easily comprehensible. As mentioned before, the text should add a few more chapters for the course instructors to select from. However, due to the succinct nature of the book, some sections seemed lacking. The text is logical and has flow. A cross tabulation (or crosstab) report is used to analyze the relationship between two or more variables. The prose is accessible and each chapter proceeds methodically. In some disciplines, thinking in terms of order of magnitude is the de facto standard. This book provides an introductory and broad review of some of the key topics in social science research including research theories, research design, data collection, data analysis and research ethics Students from different disciplines in social science will find these topics useful in developing their research method skills. This book is based on my lecture materials developed over a decade of teaching the doctoral-level class on Research Methods at the University of South Florida. I think Dave C. above is suggesting a Poisson distribution for the dependent (thats y, right?) YourModel could easily be a complex 35 term Fourier series with respect to Covariates, or a radial basis function or a Chebyshev polynomial or an exponential function or any old nonlinear thingy and yet it will overall output values between 0 and 1 as it should. It is also unnecessary to always add a comma before the word because.. How to score a likert Scale Overall, however, the author has presented a lot of information succinctly and I look forward to using this text (in parts) in future methods courses. This ties in with my comments on consistency. Thats how statistics is still taught. A survey was held among 388 applicants for unemployment benefits. The text and examples provided in it are not culturally insensitive or offensive in any way. To address this deficit, I have devoted entire chapters to topics such as Thinking Like a Researcher and Theories in Scientific Research, which are essential skills for a junior researcher.Second, the book is succinct and compact by design. I usually do this when modelling counts of animals, especially when counts can be zero, essentially modelling the count/surveyEffort. What was the number of days where the temperature ranged between the two values? The content of the text is not culturally insensitive, and the author does not present any offensive statements or comments anywhere in the text. The book is clear and has high readability. Regarding navigation, the pdf online version does not allow for creative navigation through the document. I cant really picture an example where Id want to do the transformation to the -1/8th power or the 0.39 power or whatever, and the idea of estimating the transformation from the data alone sounds like a disaster. In general, I think this textbook would be best suited to a course where the textbook is seen as an overview to supplement course discussions rather than a detailed coverage of research methods principles. Im not claiming that imputing a reasonable low number always works. Its also possible to treat some of these observations with censoring, but that just throws away information if you actually have it and if you dont have a wide enough error scale (wide enough tails, for example), itll be biased predictively. It is used to answer questions on relationships within measurable variables with an intention to explain, predict and control a phenomena (Leedy 1993). A glossary would be helpful as students often need to reference basic definitions as they learn these new concepts. Im confused about what the x data is referring to here, since in the example above log(1+x) x is used for the dependent variable. If we see something unusual in a chart, we don't easily see which variable to address.

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