Student Profile
Name
Telephone
Email
Year entered into program
Any prior graduate degrees
Area of study
Date of profile update
Please provide a short (3-5 sentences) description of your research interests.
List major datasets you have previously worked with (e.g. NLSY, BRFSS, ACS, health care billing data).
-1-
Briefly describe past research experience.
Briefly describe academic research papers, technical reports, and other professional writing you have
completed. For coauthored work, explain your specific writing contributions (e.g. preparing tables).
-2-
Briefly describe professional presentation experience, such as preparing and presenting conference
posters, preparing and delivering research presentations with and/or without PowerPoint, type of
audience, and length of presentations.
Evaluate your proficiency and level of experience in the research skills below. This list covers a wide
range of skills, from those that are very common in research to those that are highly specialized and
idiosyncratic. You should expect to leave many of these potential skills unchecked, and do not be
demoralized if you check a small number of items. All of the faculty would leave many of these skills
unchecked—although each faculty member would check different rows.
In the first column (ANY), check “yes” if you have any proficiency. Leave it blank if not. In the right
column (LEVEL OF EXPERIENCE), rate your proficiency from “high proficiency” (you have used this
technique extensively in independent research), “medium proficiency” (you have used this technique in a
class and would feel comfortable doing this if you had modest guidance from a senior researcher or
project manager, and time to review textbooks or other tutorials), or “modest proficiency” (you have
encountered this in a class or through reading articles and books and are willing to invest time to learn the
skill, but you need guidance). To maintain the formatting and make it easy for faculty and
researchers to read, replace the “” with “X” in Word. See the example below:
Quantitative Data Collection Skills
X Yes
Survey design
X Yes
Finding secondary datasets and converting them into a usable format
for statistical software
X Yes
Coding primary documents to make quantitative datasets (e.g. media
articles, contracts, policy documents)
Administering lab experiments
 Yes
Administering quantitative surveys
 Yes
X Yes
Entering quantitative survey data
 high  medium X modest
 high X medium  modest
X high  medium  modest
 high  medium  modest
 high  medium  modest
X high  medium  modest
-3-
ANY
SKILL
Computer Software Skills for Quantitative Analysis
Stata
 Yes
- Opening datasets and writing basic do files
- Organizing data (e.g. merging files, reshaping files)
- Cleaning data (e.g. recoding variables, looking for missing data
and inconsistencies)
- Graphing
- Post-estimation commands (e.g. generating predicted values)
- Writing macros or functions
SAS
 Yes
- Opening datasets and writing basic syntax
- Organizing data (e.g. merging files, reshaping files)
- Cleaning data (e.g. recoding variables, looking for missing data
and inconsistencies)
- Graphing
- Post-estimation commands (e.g. generating predicted values)
- Writing macros or functions
SPSS
 Yes
- Opening datasets and writing basic syntax files
- Organizing data (e.g. merging files, reshaping files)
- Cleaning data (e.g. recoding variables, looking for missing data
and inconsistencies)
- Graphing
- Post-estimation commands (e.g. generating predicted values)
- Writing macros or functions
R
 Yes
- Opening datasets and writing basic syntax files
- Organizing data (e.g. merging files, reshaping files)
- Cleaning data (e.g. recoding variables, looking for missing data
and inconsistencies)
- Graphing
- Post-estimation commands (e.g. generating predicted values)
- Writing macros or functions
Other statistical software:
 Yes
ArcGIS
 Yes
Visual Basic
 Yes
Vensim
 Yes
Other simulation software:
 Yes
TreeAge or other decision analysis software
 Yes
Access
 Yes
Excel
 Yes
- Basic formulas using absolute and relative cell references
- Tables
- Charts
- Pivot tables
- Sorting data (e.g. filtering)
Quantitative Data Analysis Skills
Simple descriptive statistics (e.g. means, proportions)
 Yes
Using graphics for visual exploratory data analysis (e.g. examining
 Yes
skewed distributions, outliers)
OLS regression
 Yes
LEVEL OF EXPERIENCE
 high  medium  modest
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-4-
 Yes
 Yes
Logit/probit regression
Regression for count data (e.g. Poisson, negative binomial, zeroinflated negative binomial)
Tobit/Heckit regression
 Yes
Analyzing experimental data (e.g. ANOVA, ANCOVA)
 Yes
Multivariate statistics (e.g. factor analysis, MANOVA, structural
 Yes
equations modeling)
Survival analysis (e.g. proportional hazards models, survival curves)
 Yes
Time series analysis
 Yes
Analyzing complex survey data (e.g. using sampling weights)
 Yes
Differences in differences
 Yes
Resampling standard errors (e.g. bootstrap, jackknife)
 Yes
Multiple imputation for missing data
 Yes
Instrumental variables
 Yes
Forecasting
 Yes
Using panel data (e.g. fixed effects, random effects)
 Yes
Other statistical techniques:
 Yes
Quantitative Data Collection Skills
Survey design
 Yes
Finding secondary datasets and converting them into a usable format
 Yes
for statistical software
Coding primary documents to make quantitative datasets (e.g. media
 Yes
articles, contracts, policy documents)
Administering lab experiments
 Yes
Administering quantitative surveys
 Yes
Entering quantitative survey data
 Yes
Qualitative Data Collection and Analysis Skills
Collecting data in the following ways (check all that apply):
 Yes
 interviews
 focus groups
 locating primary documents
 observation (participant or non-participant)
Exposure to the following methodologies (check all that apply):
 Yes
 ethnography
 grounded theory
 action research
 case studies
 comparative case studies
 discourse analysis
 Boolean analysis
Exposure to any of the following theoretical perspectives (check all
 Yes
that apply)
 symbolic interactionism
 phenomenology
 hermeneutics
 critical theory  postmodernism
Transcribing interviews and focus groups
 Yes
Coding data using Atlas.ti
 Yes
Coding data using NVivo
 Yes
Coding data using other qualitative software:
 Yes
Literature Review and Document Searching Skills
Locate statutes, regulations, and other policy documents
 Yes
Locate academic articles
 Yes
Conduct a systematic literature review
 Yes
Summarize academic and non-academic literature for a lay audience
 Yes
(describe fields where you feel comfortable doing this)
 Yes
 Yes
Organize references in EndNote
Other reference manager software (e.g. Zotero):
 high  medium  modest
 high  medium  modest
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-5-
Project Management and Coordination Skills
Project management roles (check all that apply):
 Yes
 developed timelines  assigned tasks to research assistants
 supervised students
 track budgets and spending
 prepare reports to sponsors
Project coordination roles (check all that apply):
 Yes
 organized meetings  organized conferences  organized seminars
 prepare meeting agendas and minutes
 other organizational roles:
Human subjects research IRB applications (check all that apply):
 Yes
 prepared IRB application  drafted informed consent statement
Other Skills Not Listed Above
Briefly describe any other research skills not covered above:
 Yes
 high  medium  modest
 high  medium  modest
 high  medium  modest
 high  medium  modest
-6-
SAMPLE
Name
Rocky Feller
Telephone
518-123-4567
Email
rfeller@albany.edu
Year entered into program
2010
Any prior graduate degrees
MA in political science
Area of study
Public Policy
Date of profile update
May 7, 2013
Please provide a short (3-5 sentences) description of your research interests.
I am interested in human services policies, including health policy and education policy. My dissertation
will use GIS modeling to evaluate how physical proximity to disco clubs is related to health outcomes,
and the political factors associated with local ordinances on disco club restrictions. Outside my
dissertation, I am interested in how the SUNY 2020 program will affect access to graduate scholarships
and graduation rates.
List major datasets you have previously worked with (e.g. NLSY, BRFSS, ACS, health care billing data).
I have worked with the TIGER/Line shapefiles from the US Census Bureau, the Behavioral Risk Factor
Surveillance System (BRFSS) from the CDC, and administrative admissions data from UAlbany
-7-
Briefly describe past research experience.
Prior to coming to UAlbany, I worked with Professor Remus Lupin at Syracuse on a project to evaluate
werewolves’ integration into New York society. I conducted semi-structured interviews with 36 Upstate
werewolves and assisted Professor Lupin with coding the data in Atlas.ti software. As a follow-up
project, I administered mail and telephone surveys about public perceptions about werewolves to
Syracuse parents. I was responsible for organizing the mailing, including reminder postcards and
collecting the survey instruments. I contacted non-responders by telephone. I also entered all of the data
using a scanner, and did simple descriptive statistics (means and percentages) in SPSS.
Briefly describe academic research papers, technical reports, and other professional writing you have
completed. For coauthored work, explain your specific writing contributions (e.g. preparing tables).
My literature review paper is in the revise & resubmit stage at Disco Quarterly. It is coauthored with my
adviser but I took the lead in drafting it and preparing all of the tables. When I first started my PhD
program, I had a research assistant assignment with Professor Plum. I assisted him with his manuscript
about the similarities of apples and oranges. Under his guidance, I located relevant academic literature
and organized the studies into an Excel sheet so that he could more easily see what had already been
published on the topic. Professor Plum handed me a large document with his Stata output, and I was in
charge of turning the Stata output into tables that were suitable for publication. Finally, I did a community
outreach project with a local disco club and put together a 2-page fact sheet for them about how discoing
can improve personal health and increase longevity.
-8-
Briefly describe professional presentation experience, such as preparing and presenting conference
posters, preparing and delivering research presentations with and/or without PowerPoint, type of
audience, and length of presentations.
I have been to APPAM a couple of times, although I only had a poster presentation and not a podium
presentation. I prepared the posters. However, I have had a lot of speaking experience as a PAD 504
instructor for the past two years. I rely on both PowerPoint slides as well as doing hands-on lab tutorials
and some white board-based discussions. I have also led a few information sessions on the health effects
of discos for the lay public in Albany.
Evaluate your proficiency and level of experience in the research skills below. This list covers a wide
range of skills, from those that are very common in research to those that are highly specialized and
idiosyncratic. You should expect to leave many of these potential skills unchecked, and do not be
demoralized if you check a small number of items. All of the faculty would leave many of these skills
unchecked—although each faculty member would check different rows.
In the first column (ANY), check “yes” if you have any proficiency. Leave it blank if not. In the right
column (LEVEL OF EXPERIENCE), rate your proficiency from “high proficiency” (you have used this
technique extensively in independent research), “medium proficiency” (you have used this technique in a
class and would feel comfortable doing this if you had modest guidance from a senior researcher or
project manager, and time to review textbooks or other tutorials), or “modest proficiency” (you have
encountered this in a class or through reading articles and books and are willing to invest time to learn the
skill, but you need guidance). To maintain the formatting and make it easy for faculty and
researchers to read, replace the “” with “X” in Word. See the example below:
Quantitative Data Collection Skills
X Yes
Survey design
X Yes
Finding secondary datasets and converting them into a usable format
for statistical software
X Yes
Coding primary documents to make quantitative datasets (e.g. media
articles, contracts, policy documents)
Administering lab experiments
 Yes
Administering quantitative surveys
 Yes
X Yes
Entering quantitative survey data
 high  medium X modest
 high X medium  modest
X high  medium  modest
 high  medium  modest
 high  medium  modest
X high  medium  modest
-9-
ANY
SKILL
Computer Software Skills for Quantitative Analysis
X Yes
Stata
- Opening datasets and writing basic do files
- Organizing data (e.g. merging files, reshaping files)
- Cleaning data (e.g. recoding variables, looking for missing data
and inconsistencies)
- Graphing
- Post-estimation commands (e.g. generating predicted values)
- Writing macros or functions
SAS
 Yes
- Opening datasets and writing basic syntax
- Organizing data (e.g. merging files, reshaping files)
- Cleaning data (e.g. recoding variables, looking for missing data
and inconsistencies)
- Graphing
- Post-estimation commands (e.g. generating predicted values)
- Writing macros or functions
X Yes
SPSS
- Opening datasets and writing basic syntax files
- Organizing data (e.g. merging files, reshaping files)
- Cleaning data (e.g. recoding variables, looking for missing data
and inconsistencies)
- Graphing
- Post-estimation commands (e.g. generating predicted values)
- Writing macros or functions
R
 Yes
- Opening datasets and writing basic syntax files
- Organizing data (e.g. merging files, reshaping files)
- Cleaning data (e.g. recoding variables, looking for missing data
and inconsistencies)
- Graphing
- Post-estimation commands (e.g. generating predicted values)
- Writing macros or functions
Other statistical software:
 Yes
X Yes
ArcGIS
Visual Basic
 Yes
Vensim
 Yes
Other simulation software:
 Yes
TreeAge or other decision analysis software
 Yes
Access
 Yes
X Yes
Excel
- Basic formulas using absolute and relative cell references
- Tables
- Charts
- Pivot tables
- Sorting data (e.g. filtering)
Quantitative Data Analysis Skills
X Yes
Simple descriptive statistics (e.g. means, proportions)
X Yes
Using graphics for visual exploratory data analysis (e.g. examining
skewed distributions, outliers)
X Yes
OLS regression
LEVEL OF EXPERIENCE
 high X medium  modest
 high X medium  modest
 high X medium  modest
 high X medium  modest
 high  medium X modest
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-10-
X Yes
X Yes
Logit/probit regression
Regression for count data (e.g. Poisson, negative binomial, zeroinflated negative binomial)
Tobit/Heckit regression
 Yes
Analyzing experimental data (e.g. ANOVA, ANCOVA)
 Yes
Multivariate statistics (e.g. factor analysis, MANOVA, structural
 Yes
equations modeling)
Survival analysis (e.g. proportional hazards models, survival curves)
 Yes
Time series analysis
 Yes
X Yes
Analyzing complex survey data (e.g. using sampling weights)
Differences in differences
 Yes
Resampling standard errors (e.g. bootstrap, jackknife)
 Yes
Multiple imputation for missing data
 Yes
X Yes
Instrumental variables
Forecasting
 Yes
Using panel data (e.g. fixed effects, random effects)
 Yes
X Yes
Other statistical techniques: spatial analysis
Quantitative Data Collection Skills
X Yes
Survey design
X Yes
Finding secondary datasets and converting them into a usable format
for statistical software
X Yes
Coding primary documents to make quantitative datasets (e.g. media
articles, contracts, policy documents)
Administering lab experiments
 Yes
X Yes
Administering quantitative surveys
X Yes
Entering quantitative survey data
Qualitative Data Collection and Analysis Skills
X Yes
Collecting data in the following ways (check all that apply):
X interviews
 focus groups
X locating primary documents
 observation (participant or non-participant)
Exposure to the following methodologies (check all that apply):
 Yes
 ethnography
 grounded theory
 action research
 case studies
 comparative case studies
 discourse analysis
 Boolean analysis
Exposure to any of the following theoretical perspectives (check all
 Yes
that apply)
 symbolic interactionism
 phenomenology
 hermeneutics
 critical theory  postmodernism
X Yes
Transcribing interviews and focus groups
X Yes
Coding data using Atlas.ti
Coding data using NVivo
 Yes
Coding data using other qualitative software:
 Yes
Literature Review and Document Searching Skills
Locate statutes, regulations, and other policy documents
 Yes
X Yes
Locate academic articles
X Yes
Conduct a systematic literature review
X Yes
Summarize academic and non-academic literature for a lay audience
(describe fields where you feel comfortable doing this)
Health policy
X Yes
X Yes
Organize references in EndNote
Other reference manager software (e.g. Zotero): Zotero
 high X medium  modest
 high  medium X modest
 high  medium  modest
 high  medium  modest
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 high  medium X modest
X high  medium  modest
-11-
Project Management and Coordination Skills
Project management roles (check all that apply):
 Yes
 developed timelines  assigned tasks to research assistants
 supervised students
 track budgets and spending
 prepare reports to sponsors
X Yes
Project coordination roles (check all that apply):
 organized meetings  organized conferences  organized seminars
X prepare meeting agendas and minutes
 other organizational roles:
X Yes
Human subjects research IRB applications (check all that apply):
X prepared IRB application X Yes drafted informed consent
statement
Other Skills Not Listed Above
X Yes
Briefly describe any other research skills not covered above:
 high  medium  modest
 high  medium X modest
 high X medium  modest
 high  medium  modest
As part of my werewolves integration project, I did extensive diversity
training in order to be sensitive about how this marginalized group
feels excluded
-12-