Ken
Frank's Web Site
Research
How
it all comes together: Integrated
statement I study the social structures of organizations and systems. How do the structures evolve, how do they affect what an organization does? I often use quantitative methods drawing on social networks and multilevel models . Typically I study small systems, in particular schools as organizations, a topic that is part of the sociology of education. Recently I've been working with the Add Health data. Check out the new teachers in social media website! Causal Inference and Robustness
Indices For Impact Threshold of a Confounding Variable and % Bias to Invalidate an Inference (can be applied to output from Stata,SAS,SPSS,R) Presentations quick examples
[pdf of quick
examples] 30 Minutes powerpoint for combined frameworks 3 hours (pdf) powerpoint for replacement of cases [pdf of
replacement of cases] 2 hours full
publishable write-up for case replacement powerpoint for correlation framework [pdf of
correlation framework] 1 hour full
publishable write-up for correlation powerpoint for Case
Replacement for Logistic Regression 10 minutes powerpoint for ordered
thresholds relative to transaction costs 10 minutes powerpoint for
alternative scenarios and related techniques 15 minutes powerpoint for comparison of frameworks [pdf of
comparison of frameworks] The value of controlling for
pretests Software Documentation for R Shiny app
KonFound-it spreadsheet
for calculating indices [KonFound-it!©] STATA Issue the following commands in STATA: . ssc install konfound . ssc install moss . ssc install matsort . ssc install indeplist Then you can
run a regression and quantify the sensitivity. . use
https://msu.edu/~kenfrank/p025b.dta, clear . regress y1 x1 x4 . konfound x1 Example data sets
Anscombe’s Quartet.dta (courtesy of CHATTERJEE, HADI, & PRICE)
Anscombe’s Quartet.rds (courtesy of CHATTERJEE, HADI, & PRICE) You can also copy into
c:\ado\personal (created by Ran Xu) PKonFound (sensitivity for published results) KonFound (sensitivity
for a user run model in Stata) Requires:
. ssc
install indeplist . ssc install matsort MKonFound (meta sensitivity across multiple studies) SAS program for calculating indices and related
measures Articles The Impact of a Confounding Variable on a Regression Coefficient
When one reports a regression from an observational study, there is always the concern: "But have you controlled for xxx?" In this article, I index the impact of a confounding variable in terms of the product of two correlations (correlation between the confounding variable and the predictor of interest X correlation between the confounding variable and the outcome -- see figure below). This product appears in both the estimate of a regression coefficient and its standard error. Thus it can be used to quantify the impact necessary to alter a statistical inference. In the article I develop the index for the bivariate and multivariate contexts, compare it to other statistics, apply to an example, describe a reference distribution, and then interpret in the context of recent concerns about causal and statistical inferences. see also Pan, W., and
Frank, K.A. (2004). "An Approximation to the Distribution of the Product
of Two Dependent Correlation Coefficients." Journal of Statistical
Computation and Simulation, 74, 419-443 Frisco,
Michelle, Muller, C. and Frank, K.A.
2007. Using propensity scores to study changing family structure and academic
achievement. Journal of Marriage
and Family. Vol 69(3):
721–741 Concerns about Causality in the Network Influence Model
Representation of Social
Structure I have analyzed the social networks of teachers in a school, and how that links to teachers' background characteristics and their orientations to teaching {see the figure below}. For related articles, see: Frank. K.A. 1995. Identifying
Cohesive Subgroups. Social Networks (17): 27-56 Frank, K. A.
and Yasumoto, J. 1996. "Embedding Subgroups in
the Sociogram: Linking Theory and Image". Connections 19 (1): 43-57
. Jaeger-Miehls, A. L., Mason, D. M., Frank,
K.A., Krause, A. E., Peacor, S.D., and Taylor, W.W.
2009. Invasive species impacts on ecosystem structure and function: A
comparison of Oneida Lake, New York, USA, before and after zebra mussel
invasion. Ecological
Modeling. Jaeger-Miehls, A. L., Mason, D.
M., Frank, K.A., Krause, A. E., Peacor, S.D., and Taylor, W.W. 2009. Invasive species
impacts on ecosystem structure and function: A comparison of the Bay of Quinte, Canada, and Oneida Lake, USA, before and after
zebra mussel invasion. Ecological
Modeling. Shaffer, David Williamson, David Hatfield,
Gina Navoa Svarovsky,
Padraig Nash, Aran Nulty,
Elizabeth Bagley, Ken Frank,
André A. Rupp, Robert Mislevy. 2009.
Epistemic Network Analysis: A Prototype for 21st-Century Assessment of
Learning. International Journal of Learning and Media 1(2):33-53.
Regarding the above figure, in Frank, K. A.
(1998). "The Social Context of Schooling: Quantitative Methods" Review
of Research in Education, Vol, 23, chapter 5, pages 171-216. I wrote: The figure establishes a basis for
integrating qualitative data and information from survey instruments to
characterize the processes through which teachers are affected by their
social contexts. As indicated in school documents, at "Our Hamilton
High," the student population has become increasingly disadvantaged over
the years, as poor families have moved to the district from a nearby city and
as the children of the more established wealthier families have aged. The
teachers have responded in various ways to this exogenous change. Some who had
difficulty adapting to the change sought early retirement. Others altered
their mode of relating to thestudents, befriending
the students whom they felt were most in need. In this sense the school is
like others described by (Grant, 1988) and (Metz, 1990). A core of teachers
relate to the new types of students by acting as "moral agents,"
inculcating students into a specific set of values emphasizing citizenship
and responsibility by keeping firm control of the classroom and through
personal example (see Bidwell, et al., 1997, for a definition and
operationalization of moral agency in terms of responses to survey items,
reliability=.74).
Adolescent Social Contexts in
Schools I am part of the AHAA project that supplements the Add Health Data base with information from high school student transcripts. With Sam Field, I adapted my clustering algorithm to two-mode data (e.g., students and courses) Frank,
K.A., Muller, C., Mueller, A.S., 2013. The Embeddedness of
Adolescent Friendship Nominations: The Formation of Social Capital in
Emergent Network Structures. American Journal of Sociology, Vol
119(1):216-253. Media hits: Atlantic;
Huffington
Post; Huffington
Post (Op-ed); US
News and World Report; Yahoo;
Health
Day; RedOrbit; The
Times of India; MSUToday: Psych
Central: Positions
and Promotions; Deccan
Chronicle: wood
radio: Fox
Chicago: local
news channels (south Carolina): Science
Daily; National
Science Foundation models for ensemble estimation Barrett, Jennifer; Pearson, Jennifer; Muller; Chandra; Frank, K.A. 2007. “Adolescent Religiosity and School Contexts” Social Science Quarterly, Vol 88(4): 1024-1037. *Field, S.
*Frank, K.A., Schiller, K, Riegle-Crumb, C, and Muller, C. (2006).
"Identifying Social Contexts in Affiliation Networks: Preserving the
Duality of People and Events. Social Networks 28:97-123
The Social
Organization of the School Spillane, J., Kim, Chong Min, Frank, K.A. 2012. “Instructional Advice and Information Providing and Receiving Behavior in Elementary Schools: Exploring Tie Formation as a Building Block in Social Capital Development.” American Educational Research Journal. Vol 49 no. 6 1112-1145 Frank, K.A.
2014. “Constitution for effective School Governance.” Shanker Institute Blog Penuel, W., Riel,
M., Krause, A., & Frank, K. A. 2009. Analyzing Teachers' Professional Interactions in a
School as Social Capital: A Social Network Approach. Teachers College Record
Vol 111 Number 1. Figures
EEPA Spillover Effects of PD Social Factors and
Implementation of Innovations in Organizations Instruments and related resources Masuda,
Yuta J., Liu, Y., Reddy, S.M.W., Frank,
K.A., Burford, K. (2018). Informal boundary spanners for
intraorganizational innovation
diffusion for sustainability. Nature:
Sustainability, 1: 190-197. http://rdcu.be/Kre4 Frank, K.A., Penuel, W.R., Krause, A (2015). What is a “Good” Social Network for
Policy Implementation?: The Flow of Know-How for Organizational Change. Journal of Policy Analysis and Management. Early view: http://onlinelibrary.wiley.com/doi/10.1002/pam.21817/abstract Frank,
K.A. Lo, Y., Sun, M. 2014. “Social
network analysis of the influences of educational reforms on teachers’
practices and interactions.” Zeitschrift für Erziehungswissenschaft.
Volume 17 , Issue 5, supplement: 117-134. Related
ppt: What We Know About Teacher and Administrator Networks for BNU 8-14-14 Frank*, K.A., Penuel*, W.R., Sun, M. Kim, C., and Singleton, C. 2013. “The Organization as a Filter of Institutional Diffusion. Teacher’s College Record. *Authors listed alphabetically – equal authorship. Volume 115(1). http://www.tcrecord.org/Content.asp?ContentID=16742 Penuel, W.R.,
Sun, M., Frank, K.A., & Gallagher, H.A. 2012. Using social network
analysis to study how collegial interactions can augment teacher learning
from external professional development. American Journal of
Education, 119(1), 103-136. Youngs, P., Frank, K.A., Thum, Y.M., & Low, M. 2012. The motivation of teachers to produce human capital and conform to their social contexts. In T. Smith, L. Desimone, & A.C. Porter (Eds.), Yearbook of the National Society for the Study of Education: Vol. 110. Organization and effectiveness of high-intensity induction programs for new teachers (pp.248-272). Malden, MA: Blackwell Publishing. Penuel, W. R., Frank, K.A., Sun, M., and Kim, C. 2012. Teachers’ Social capital and the Implementation of Schoolwide Reforms. Pages 183-200 in Sean Kelly, Editor. Understanding Teacher Effects. New York: Teachers’ College Press. Youngs, P., Frank, K.A., and Pogodzinski, B. 2011. The Role of Mentors and Colleagues in Beginning Elementary and Middle School Teachers’ Language Arts Instruction. Chapter 8 in Sean Kelly, Editor. Understanding Teacher Effects. New York: Teachers’ College Press. Penuel, W.R., Frank, K.A., and Krause, A. 2010.
Between Leaders and Teachers: Using Social Network Analysis to Examine the
Effects of Distributed Leadership.
Pages 159-178 in Alan J. Daly
editor. Social Network Theory and Educational Change. Cambridge:
Harvard University Press. Penuel, W. R., Riel, M., Joshi, A., & Frank, K. A. 2010. The alignment of the informal and formal supports for school reform: Implications for improving teaching in schools. Educational Administration Quarterly, 46(1), 57-95. Zhao, Y., Lei, J., & Frank. K. 2005. Theoretical Innovation and Empirical Testing: Research Design in Educational Technology. In Li, F. L. (ed). Research Methods in Computers for Education (jisuanji jiaoyu yanjiu fangfa). Beijing, China: Beijing Normal University Press. Zhao, Y., Frank, K., & Ellefson, N. (2006). Fostering Meaningful Teaching and Learning with Technology pages 161-179 in Floden R. & Ashburn, E. (Eds.). Meaningful Learning Using Technology What Educators Need to Know and Do. Teachers College Press. National Board Certified Teachers Anagnostopoulos, D., Sykes, G., McCrory, R., Cannata, M., Frank, K.A. 2010. “Distinction, or Duty? The Meaning of the National Board of Professional Teaching Standards for Teachers' Work and Collegial Relations. American Journal of Education.. v116 n3 p337-369. Chaos and Complexity in Organizations Kyle Fahrbach and I modeled how people influence one another and choose with whom to interact. The combination of these processes can generate a range of equilibria characteristic of the complex system of organizational culture. See Xu, R, and Frank,
K. A. (2016). The Implications for Network Structure of Dynamic
Feedback between Influence and Selection. In International
Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction.
Springer International Publishing.
Myazaki, Yasuo and Frank, K.A. (2005). "A Hierarchical Model with Factor Analysis Structure at Level 2" Journal of Educational and Behavioral Statistics Frank, K.A. and Yasumoto, J. 1998. "Linking Action to Social Structure within a System: Social Capital Within and Between Subgroups." American Journal of Sociology 104 (3): 642-686. (see Jstor) Frank, K. A.
1998. "The Social Context of Schooling: Quantitative Methods".
Review of Research in
Education 23, chapter 5: 171-216. Bidwell, C. E., Frank, K.A., and Quiroz, P. 1997. "Teacher Types, Workplace Controls, and the Organization of Schools." Sociology of Education, 70 (4): 285-307. (see Jstor) Frank, K.A. 1993. Identifying Cohesive Subgroups. Unpublished Doctoral Dissertation, University of Chicago. Bryk, A.S. & Frank, K.A. 1991. "The Specialization of Teachers' Work: An Initial Exploration." In Schools, Classrooms, and Pupils, edited by S.W. Raudenbush, S. W., and J.D. Willms. New York: Academic Press (Harcourt Brace Jovanovich).
With multiple coauthors from Fisheries and Wildlife, I have written about how human networks are at the intersection of global networks and the networks of ecosystems Responses re: causal inference Conceptualizing and Measuring Environmentalism Frank, K.A., Chen, I-Chien., Lee, Youngmi; Kalafatis, Scott; Chen, Tingqiaol; Lo, Yun-jia; Lemos, Maria. 2012. Network Location and Policy-Oriented Behavior: An Analysis of Two-Mode Networks of Co-authored Documents Concerning Climate Change in the Great Lakes Region. Policy Studies Journal. Volume 40, Issue 3, pages 492–515. Recent ppt relating networks to beliefs about lake levels and freeze-thaw cycles in the Great Lakes. N. J. Leonard, W. W. Taylor, C. I. Goddard, K. A. Frank, A. E. Krause & M. G. Schechter. 2011. Information Flow within the Social
Network Structure of a Joint Strategic Plan for Management of Great Lakes
Fisheries, North American Journal of
Fisheries Management, 31:4, 629-655. Available: http://dx.doi.org/10.1080/02755947.2011.603651 Kenneth Frank received his Ph.D. in measurement, evaluation and statistical analysis from the School of Education at the University of Chicago in 1993. He is currently a professor in Counseling, Educational Psychology and Special Education as well as in Fisheries and Wildlife and adjunct in Sociology at Michigan State University. His substantive interests include the study of schools as social organizations and the social embeddedness of natural resource use. His substantive areas are linked to several methodological interests: social network analysis, causal inference and multi-level models. His publications include quantitative methods for representing relations among actors in a social network, robustness indices for inferences, and the effects of social capital in schools and other social contexts. He teaches general introductory courses in research methods and quantitative methods as well as advanced courses in multivariate analysis and seminars in social network analysis and causal inference. Ken’s current projects include a study of the effects of the Michigan Merit Curriculum on educational outcomes and how knowledge about climate change diffuses to policy-makers and educators. |
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