Blog Index- December

Current to 12/30 

Topic	Dates of Posts
Dissertation, general	7/5, 8/16, 8/19, 9/27, 10/2
Selecting a Topic	4/23, 7/8, 7/10
Organization	4/22, 10/2
Committee Members	4/17, 5/3, 6/10, 7/19, 8/21
URR	5/8, 5/27
Center for Research Quality	12/9
Overview of Process	4/19, 9/18, 12/13
Premise	4/17, 9/6
Proposal	4/22, 9/9
Research questions	10/9
C. 1	5/6, 10/21, 10/23, 10/25, 10/28, 11/1
C. 2 (literature related)	4/26, 5/29, 6/3, 6/12, 6/17, 6/28, 9/16, 10/11, 11/4, 11/6, 11/9, 11/15
C. 3	5/1, 10/16, 10/28, 11/18, 11/20, 11/22, 11/25, 12/2, 12/4, 12/6, 12/11, 12/16, 12/18, 12/20, 12/23, 12/27
Defense	4/23, 5/8
IRB	5/10, 10/14
Data Collection	5/13, 5/15, 10/16
Quantitative	5/17, 7/24, 7/26, 7/29, 7/31, 8/2, 8/5, 10/4, 10/7, 11/20, 12/2, 12/4, 12/6, 12/18, 12/23, 12/27
Qualitative	5/20, 11/20, 11/22, 11/25, 12/11, 12/16
Mixed Methods	5/22, 11/18, 11/20, 11/22, 11/25, 12/11, 12/20, 12/23, 12/27
C. 4	517, 5/20, 5/22, 7/17
C. 5	5/24, 9/20, 10/11
Final Defense	4/23, 5/27/ 9/11
Career	7/12
Goal Form	8/12
Motivation	6/5, 6/26, 7/1, 8/16, 8/23, 9/2, 9/18, 10/18, 11/8, 11/27
Secondary Data	5/31
Support, Getting	4/26, 6/5, 6/24, 8/16
Writing	4/26, 4/29, 6/12, 6/21, 7/3, 8/9, 8/14, 9/4, 9/23,9/25
Other	4/18, 6/7, 6/14, 6/19, 6/24, 6/26, 7/1, 7/8, 7/15, 7/19, 7/22, 8/7, 8/16, 8/19, 8/26, 8/28, 8/30, 9/2, 9/13, 9/18, 10/18, 11/27, 12/13, 12/25

 

Next time I will take a look at the new year. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu

Chapter 3: Threats to Validity- internal validity quant and mixed methods

Previously we looked at external validity in quantitative and mixed methods studies, today we look at internal validity. Internal validity refers sto whether an experimental treatment/condition makes a difference or not, and whether there is sufficient evidence to support the claim. Some threats to internal validity include: 

•History--the specific events which occur between the first and second measurement. People are affected by elements outside of the study. Let's use an extreme example of this, say you were interested in fear of flying and gave people a survey examining this variable on Sept 9, 2001. The participants then went through a de-sensitization training for a week and came back on Sept 16, 2001 and were retested. They are also going to be affected by an historical event outside of the study- the traumatic events of 9/11, and you would need to account for this.  

•Maturation--the processes within subjects, which act as a function of the passage of time. i.e. if the project lasts a few years, most participants may improve their performance regardless of treatment. As people age they change, so if you were doing a study that lasted any period of time, you need to realize that they will change without your intervention. This is often why a control group is used, so the normal changes that occur can be compared with those of the treatment. 

•Testing--the effects of taking a test on the outcomes of taking a second test. Simply taking a test can change how people think, they also cannot forget what they read in the first test. So if you give a second test people will have thought about their first answers and may change them in the second test because of that thinking process.  

•Instrumentation--the changes in the instrument, observers, or scorers, which may produce changes in outcomes. Many things can affect the results, minor changes in wording, having additional people in the testing area, having different people score the test all may change the results. 

•Statistical regression--It is also known as regression to the mean. This threat is caused by the selection of subjects on the basis of extreme scores or characteristics. Give me forty worst students and I guarantee that they will show immediate improvement right after my treatment, not because of my great treatment, but because they expect to do better.  

•Selection of subjects--the biases which may result in selection of comparison groups. Randomization (Random assignment) of group membership is a counter-attack against this threat. However, keep in mind that randomization is only effective with large samples.  

•Experimental mortality--the loss of subjects. For example, if you require people to participate in multiple training sessions, some will drop out. Those who stay in the project all the way to end may be more motivated to learn and thus achieved higher performance.  

•Selection-maturation interaction--the selection of comparison groups and maturation interacting which may lead to confounding outcomes, and erroneous interpretation that the treatment caused the effect. A great example is if you had girls in a class assigned to one treatment and the boys assigned to another treatment. You compare them and discover there is a treatment difference. However, you do not know if it is the treatment that caused the differences or was it any differences in development between the girls and the boys. 

In this section of your paper, you need to think through the various internal validity issues and how you will address them. 

Next time I will post an updated index. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu 

Completing the Dissertation; My View from the Finish Line

Today, in honor of Christmas, we have a guest writer, Susan Ruiz, Ph.D. Susan recently completed her dissertation at Walden and shares with us her view from the finish line. 

As I look back over this journey, I have come to realize that there were certain key points that forever changed the progress that led to the completion of my dissertation:  

1. Accept that the best thing to happen to your research study is when you have partnered with a chair that is knowledgeable with the University’s policies and procedures which mandate the development of a viable research study. They are strategically in place to align your research to offset potential pitfalls behind missing or unexplained areas in your study.

2.  Any time there is a rewrite of a chapter or section of your dissertation, accept that revisions are going to be required and that if you are susceptible to vocalizing frustrations- check your attitude and apologize. Your chair and your committee are there to ensure that the very best project will develop under their guidance.  They have worked through their own dissertation and probably understand better than anyone, the frustrations behind revisions.    

3. While no one truly enjoys waiting, it is important to consider your frustrations as you near the end and begin your preparation to defend your study. Once the defense, and all the reviews and revisions are behind you, exhale. You are finally done writing your dissertation. The next few emails will be recognition of your completed study, the steps to publish in ProQuest. Before you realize the pace- someone will call you, “Dr.” 

While working through years of dissertation development, the doctoral degree seemed out of reach, something I strove to attain but the magnitude of this accomplishment is that completing the dissertation was only the beginning! Now that I have completed my journey, I look forward to new studies, new information that will continue the research I started in my dissertation.  Being done is not the time to fold it up, to tell yourself that you are done and that is it. No, this is the time to take on the higher heights that you once dreamed of. Remember what you told yourself you would do with this research once you are done? Now is the time to embrace your next project. The finish line for one journey is the starting line-up for the next!  

Once you have completed your journey, seek continued mentorship with others who have been engaged in your specialization. Glean from their wisdom and insight- continue to learn how successful people accomplish their goals beyond the dissertation.  Above all, be willing to entertain the questions and inquiries from others who are still on their journey- share how you managed the steps in your dissertation, as it is possible that you experienced certain difficulties in order to be able to relate to someone else.  

One lasting impression I have is the realization that my study will be reviewed by other students in the years to come. The issues that were present in my population could be successfully addressed by those who take what I have started and develop new theories and methodologies. For me, there is no better legacy than this. 

Next time we will continue our review - Chapter 3: Threats to Validity- internal validity. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu

Chapter 3: Threats to Validity: external validity – quantitative and mixed methods studies

The threats to validity section in the quantitative and mixed methods checklist is one of the trickiest to understand. Let's see if I can make some sense of it for you. It begins with threats to external validity. External validity is the extent to which the researcher can conclude that results apply to a larger population (generalizability). Here are some common threats to external validity. 

•Reactive or interaction effect of testing--a pretest might increase or decrease a subject's sensitivity or responsiveness to the experimental variable. Therefore, giving a pretest changes your participants, they will respond differently later because they took the pretest. 

•Interaction effects of selection biases and the experimental variable. You may unintentionally choose people that have particular biases. For example if you are doing an online survey about use of the internet- you will only have people participate who are already comfortable enough with the computer and internet to choose to participate in an online survey. You will be missing people who are not comfortable with computers. 

•Reactive effects of experimental arrangements--it is difficult to generalize to non-experimental settings if the effect was attributable to the experimental arrangement of the research. So, if you are doing some type of experiment in a controlled setting (picture a quiet psychology lab room), there is no way to know what will happen when a similar occasion occurs in the real world. 

•Multiple treatment interference--as multiple treatments are given to the same subjects, it is difficult to control for the effects of prior treatments. People cannot "unlearn" something, so whatever has happened to them previously will affect future learning/ experiences. 

In this section of chapter 3, you need to think through what are the threats to external validity in your study. Keep in mind that no study is perfect, it is ok, in fact, it is expected that there will be issues. The important thing is that you recognize them. 

Next time, in honor of Christmas, we will have a guest writer, Dr. Susan Ruiz. She is a recent Walden grad who will share with you some of her experiences. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu 

Chapter 3: Instrumentation in mixed methods studies

For mixed methods, the instrument section has to accommodate both qual and quant instruments. For the qualitative components, identify each instrument (observation sheet, interview protocol, focus group protocol, videotape, audiotape, artifacts, archival data, and other kinds of data collection instruments). State the source of each item and provide the permission for it in your appendix.  

For published instruments, identify who developed it, where and with what populations it has been used. State why you think it is appropriate for your study, and any cultural or context issues that might be present with your population. 

If you are designing qualitative instruments, explain how you developed them – what was the basis for them? How will you establish content validity? 

Similarly, for the quantitative components, explain the background of each instrument. Discuss validity and reliability in previous studies and where it has been used before. 

See my comments 12/18 on developing your own quantitative instrument. The next section is how you will recruit participants for each component (qual and quant). Go into detail on how and where the data will be collected for each component.  

Finally, you need to lay out your data analysis plan for each component. For the quantitative aspects, indicate your hypotheses and what statistical tests will be used for each. How will you interpret the results? For the qualitative portion, indicate how you will code the transcripts and how you will handle discrepant cases. Then you need to integrate the two types of data and compare their results. How will you do this? Many students do a figure illustrating their analysis plan for mixed methods studies, you might find this helpful.

Next time we will continue our review - Chapter 3: Threats to Validity. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu

Chapter 3: Instrumentation in quantitative studies

Last time we looked at instrumentation in qualitative studies, this time we move to quantitative studies. Generally, students will be relying on previously published instruments for quantitative studies. I do not recommend developing new surveys for a doctoral study. I will explain more on this below. 

You will begin this section by discussing each instrument you will be using, who developed it and when. Then indicate why you have chosen it, and why it is appropriate for your study. You will need permission to use the instrument from the developer- include it in your appendix. Then go into detail about the published validity and reliability values that are relevant for your study (those using similar populations). Finally, you will discuss when and with what populations it has been used and how validity and reliability were established for each study. 

If you are developing your own instrument, first describe the basis for its development. Did it come through items indicated in the literature? Did you or plan to do a pilot study to refine the questions? You will need to provide evidence for its reliability and validity, this typically requires extensive testing (100s of participants). Finally, show how the instrument will answer your research questions. If you are developing your own instrument, it will require quite a bit of testing and additional work; again, I do not recommend this for a dissertation. 

If you are doing an intervention involving manipulation of an independent variable, please see my post on 12/6, there are issues that will come up with the IRB, address them early! As far as c. 3, identify any materials that will be used in the intervention. Indicate who developed the materials and where they have been used in the past (you also may need permission from the developer to use them). If you developed them, indicate how that was done. Provide evidence that another agency will sponsor the intervention. 

Next, you need to operational each variable. So for example, if you are interested in resilience, define it and how you will be measuring it. Then talk about how each variable or score is calculated and what the scores represent. Give an example item from each scale/ subscale.  

The final portion of this section is your data analysis plan. Mention what software you will use, how you will clean the data (how you will handle missing data, and make sure there are not any extreme outliers). Restate your research questions and hypotheses from c 1. Then, for each hypothesis describe the statistical tests that will be used. If you are doing many statistical tests, you need to account for that by using a correction statistic (Bonferroni's is common- it reduces your p value, based on the number of tests). If you are using covariates and/or have confounding variables, you need to discuss it. Finally, how will you interpret the results (key parameter estimates, confidence intervals and/or probability values, odds ratios, etc.).  

Next time we will continue our review - Chapter 3: Instrumentation in mixed methods studies. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu

Chapter 3: Instrumentation in qualitative

In qualitative studies, if you are talking to people and not using archival data, you will design most of your instruments.  You need to identify each data collection instrument and provide the source of it, if you did not design it (some examples: observation sheet, interview protocol, focus group protocol) There are also archival data which would need to be identified and the source (e.g., video-tape, audio-tape, artifacts, archived data). 

If you are using historical or legal documents as a source of data (unusual to use), demonstrate the reputability of the sources and justify why they represent the best source of data. Then you want to clearly demonstrate the link between the data collection instruments and your research questions.  

For published data collection instruments.

Explain who developed the instrument and provide the date of publication. Detail where and with which participant group it been used previously. You then need to justify its use in the current study (that is, context and cultural specificity of protocols/instrumentation) and whether modifications will be or were needed.  

Describe how content validity will be or was established (how do you know it is looking at what you think it is?). A common way to do this is to use an expert panel. Discuss any context- and culture-specific issues specific to the population while developing the instrument. An example might be that if you are using an interview protocol that was designed for adults, and you want to use it with adolescents, you would need to change some of the language. 

For researcher-developed instruments

What did you use as the basis for instrument development (some examples might be from the literature or from doing a pilot study)? Again you need to describe how content validity will be or was established (how do you know it is looking at what you think it is?). Finally, you want to describe how your instruments will answer the research questions. 

Next time we will continue our review - Chapter 3: Instrumentation in quantitative studies. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu

How long should a dissertation take?

In honor of Friday the 13^th I will discuss one of the most common questions I receive: how long will it take me to do a dissertation? Of course, my answer is that it is very individual, it depends on how good of a writer you are, the type of study you do, and what problems you encounter. 

But today, let's go a little deeper. Some students get it into their head that they should be done within 5 quarters- that is, after all, what the program states is the requirement. However, this number has little to do with reality; it is simply the academic requirement. Dissertations do not go according to schedule; it will take however long it takes. Yes, I have seen students get done in 5 quarters, but I have also seen others take 2-3 years.  

Why does it take so long?? There are a number of reasons. 1) Students may not write well, requiring many revisions and working with the writing center or a private editor. 2) There are many waiting times- each person that reviews your paper has 10 business days. Therefore, if you have to do revisions, that time adds up. 3) Different research methods take different time periods. The fastest is doing an archival or secondary data analysis. Probably qualitative and mixed methods take the longest. 4) Problems arise; in fact, expect them. You may not be able get the required number of participants, your computer crashes, you or family members get sick, your boss insists that you work overtime. Things happen, which delays the process. 5) Chair or committee issues, sometimes personalities clash, committee members get sick or even die. There is no way to predict such things and they too slow you down. 

What are characteristics of students who get done quickly? They tend to be excellent writers, work every day on their paper, and the dissertation gods grant them minimal outside problems. Promise yourself today – however long it takes, you will keep working on it. That will get you done. 

Next time we will continue our review - Chapter 3: Instrumentation in qualitative studies. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu

Chapter 3: Participant Selection- qualitative and mixed methods

The section on participant selection for qualitative and mixed methods is similar to the quantitative, except you need to think of it in terms of the methodology. So again, identify your population – to whom will the results generalize (or to use the qual term - transfer)? In qualitative/ mixed method studies the population is generally smaller than quantitative, so if you are interested in women who have been in domestic violence relationships, think about what age range will be included? What geographic area? All of these issues limit the transferability. 

Identify and explain your sampling strategy. For example, will you use snowball sampling? How will that happen? How will you do your initial recruitment? Why is this the best method for your specific study? How will you know participants meet your inclusion criteria? Using the previous example, how will you know that they have been in abusive relationships? 

How many participants do you need? Why did you decide on that number (support it with literature)? For mixed methods studies, you will also need to explain how many participants you need for each aspect, and you will need a power analysis for the quantitative portion. Talk to your methodologist about this. 

Carefully describe how you will identify, contact, and recruit your participants. Be very detailed. Remember if you plan to rely on any other people/ organizations for referrals or help in any way, you will need a letter of agreement from them, spelling out exactly what they will do and provide. 

In qualitative studies, you need to consider the idea of saturation, meaning when you are not getting any new information from participants. How does this fit with your sample size? If you have not reached saturation by the time you have talked to all of your required sample, what will you do? (hint, keep doing interviews). 

Next time, in honor of Friday the 13^th I will talk about how long should a dissertation take. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu

Five Resources on the CRQ Website

Greetings. My name is Daniel Salter, and I work in the Center for Research Quality (CRQ) and am on the doctoral faculty in the Riley College of Education and Leadership. I'm also very excited to be able to provide this guest blog posting. I want to focus specifically on five resources that you can find on the CRQ website (beyond all the forms!) that can potentially support your dissertation process. All of them can be found at this link 

http://researchcenter.waldenu.edu/Research-Resources.htm 

The ICPSR 

Through the university's membership in the Inter-University Consortium for Political and Social Research (ICPSR), you have access to a ton of information that is available through various databases that are part of this service. You may find that some of this information can provide you the necessary facts and figures that you need to develop your research question in Chapter 2, and/or to answer the research question in Chapter 4. They also provide training on using large databases. 

Social Change Impact Report Datasets 

Consistent with our mission, Walden University has collected data on the impact of social change efforts on a global scale, over the past few years. We have made these datasets available to interested researchers, including students, for further use and analysis. As with the ICPSR data, you may find some information here to inform your research question, or to answer it.  

SPSS 

Even if you are the most dyed-in-the-wool, "ain't interested in crunching any numbers", qualitative researcher, you should still become familiar with data analysis software (and, it can be used for qualitative data analysis, by the way). The university makes SPSS available to current students for free, and instructions for downloading it are on our site.  

The Walden Participant Pool 

Although not appropriate for every dissertation, the Walden Participant Pool is comprised of hundreds of individuals who are willing to participate in IRB-approved research studies. The pool might be an option for some students as a resource for their sample, and is definitely something to which everyone should contribute as a participant. I actually have a study listed, and have participated in three projects thus far. You have to register for it, either way. 

Tutorials and Guides 

In the middle of the web page, we have tried to curate many of the guides and supplements that you will encounter during your experience as a doctoral student (e.g., the HAT from Residency 3). We also have developed several supplemental tutorials and videos on common topics of interest to our research community, from getting started on the project to getting your final abstract approved. Students find many of these tutorials to be excellent refreshers on topics they learned earlier. 

If you have specific questions about your dissertation for the CRQ, you can send it to research@waldenu.edu, or ask them in the comments section of this posting. You can also feel free to add +Daniel Salter to a Google+ circle, and follow the CRQ on Twitter @WaldenResearch 

Next time we will switch to qualitative and mixed methods studies and look at Chapter 3: Participant Selection. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu

Chapter 3: Additional Information, quantitative

There are three special cases that are listed in the quantitative checklist that we will examine today: a pilot study, conducting an intervention, and archival data. As you may remember from my previous post on 10/16, I am a fan of pilot studies, but you do need to explain why you are doing one and who will be participating in it. Pilot studies are typically done to give you an opportunity to practice your procedures, check the clarity of the measure, and to determine how long the full study will take (so you can report that in your consent form). 

Doing an intervention, which means introducing any new training, treatment, or information to your participants is a very tricky proposition at Walden. Even something as simple as having a control group may come under the intervention rules. So if you have been thinking along these lines, I caution you to write to the IRB today (irb@waldenu.edu) and talk to them about it. You, as the researcher, will not be allowed to do the intervention. So, some other group or institution will have to sponsor it. You are only allowed to collect the data on it. After you talk to the IRB about this, if it still makes sense to do an intervention, you will need to clearly describe what will be done and who will do it. Also, clearly indicate your role and what you will and will not be doing with it. 

Archival (or secondary) data, using already collected data in your dissertation, is a great method to use. See my blog post 5/31 for additional info on accessing it. You will need to relate all the information about how the original study was done, including recruitment and data collection. Then you will need to describe the procedure used to access the data, including any permission letters you needed (include them in the appendix). If you are using historical or legal documents (this is uncommon), describe how you know they are accurate and why they are the best possible sources to use. 

Next time we will have a guest writer, Dr. Daniel Salter from the Center for Research Quality. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu 

Chapter 3: Recruitment- quantitative

In this section, you need to think details! It must be written in enough detail that someone else could replicate the study based on your description. This is always more difficult than you think it will be, you might find it helpful to talk through the section with someone, such as a classmate or spouse. Have them push you for as many details about it as possible. 

The checklist is pretty vague in the specifics of this section. Let's start with how you will recruit- will you put up flyers? Send out emails? If you are sending out emails- where will you get the addresses? Make a note that you will need copies of all communications (flyers, emails) for the IRB and they will need to be in your paper's appendix. If you are planning to get emails from a company, institution, etc. you will need a letter of agreement from them spelling this out. 

Once people contact you, what will you say to them? This needs to be written out. If you are sending them to a survey on a website, what will it include? What demographic information will you collect? Typically, you will want to know their sex, age, and maybe socio-economic status. This is collected so you will be able to describe who your sample is. There may be other information that you will want to know to confirm their eligibility to be in the study, perhaps marital status, part or full time work, etc. 

Each participant will need to read and agree to a consent form (see the IRB website for a template). If they are completing an online survey, this is usually the first page of the survey. A copy will need to be sent to the IRB and be included in your paper's appendix. 

Next, you need to describe how the data will be collected. Again, be very specific on how this will occur. Then you need to discuss if you will debrief your participants in some way (often done in in-person studies). This is where you would thank them for participating and give them an overview of the study, if it wouldn’t have been clear before. Again, a copy will need to be sent to the IRB of the debriefing and added to the appendix. 

Finally describe any follow up procedures, such as their being contacted again in the future or having to return for any reason. 

Next time we will continue with quantitative studies and look at Chapter 3: Additional Information. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu

Chapter 3: Population and Sampling Procedures from quantitative studies

In quantitative studies, it is particularly important to understand who your population and who it is not. Therefore, the first thing to address in this section is who is your target population. Again, the best way to think about this is who does the study generalize to? So if you were testing undergraduates, that is who your population really is (contrary to many of the old studies who make the case that they are similar to the population in general). Next, you want to state approximately how large the population is that you are using. This may take some detective work to get at. 

The next section is Sampling. You rarely can test the entire population; instead, you must strategically sample to make sure you get a representative group. How will you do that? There are many ways that have been suggested, the important thing is to realize the cost and benefit of each method and how they affect your study. Let's say that you decide that you will post flyers and have people contact you if they want to participate. There are a number of costs of doing it this way: you will only get people who frequent where you are posting flyers, you will only have people who volunteer, and only people who have a phone to contact you. None of these issues are fatal flaws, but you need to be aware of them. 

What are your inclusion criteria (who can participate) and exclusion criteria (who cannot participate)? Think details. If you are doing an internet survey on survey monkey- inclusion criteria include: people who can read English, have access to a computer, as well as any issues related to your population (e.g., divorced for a year). 

You will need to do a power analysis to determine how large your sample should be. Check with your methodologist, as to whether they have a preference as to how to do it. I generally recommend using one of the power analysis calculators available online (do a search for power analysis calculator). You need to give the website that you used for the calculation and why you used the parameters that you entered. You may need to talk to your methodologist about this aspect. 

Next time we will continue with quantitative studies and look at Chapter 3: Recruitment. Do you have an issue or a question that you would like me to discuss in a future post? Would you like to be a guest writer? Send me your ideas! leann.stadtlander@waldenu.edu