11 results on '"Heeringa, Steve"'
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2. Multiple Imputation with Massive Data: An Application to the Panel Study of Income Dynamics
- Author
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Si, Yajuan, Heeringa, Steve, Johnson, David, Little, Roderick, Liu, Wenshuo, Pfeffer, Fabian, and Raghunathan, Trivellore
- Subjects
Statistics - Methodology ,Statistics - Applications - Abstract
\Multiple imputation (MI) is a popular and well-established method for handling missing data in multivariate data sets, but its practicality for use in massive and complex data sets has been questioned. One such data set is the Panel Study of Income Dynamics (PSID), a longstanding and extensive survey of household income and wealth in the U.S. Missing data for this survey are currently handled using traditional hot deck methods because of the simple implementation; however, the univariate hot deck results in large random wealth fluctuations. MI is effective but faced with operational challenges. We use a sequential regression/ chained-equation approach, using the software IVEware, to multiply impute cross-sectional wealth data in the 2013 PSID, and compare analyses of the resulting imputed data with those from the current hot deck approach. Practical difficulties, such as non-normally distributed variables, skip patterns, categorical variables with many levels, and multicollinearity, are described together with our approaches to overcoming them. We evaluate the imputation quality and validity with internal diagnostics and external benchmarking data. MI produces improvements over the existing hot deck approach by helping preserve correlation structures, such as the associations between PSID wealth components and the relationships between the household net worth and socio-demographic factors, and facilitates completed data analyses with general purposes. MI incorporates highly predictive covariates into imputation models and increases efficiency. We recommend the practical implementation of MI and expect greater gains when the fraction of missing information is large.
- Published
- 2020
3. Image processing and analysis methods for the Adolescent Brain Cognitive Development Study
- Author
-
Hagler, Donald J, Hatton, SeanN, Cornejo, M Daniela, Makowski, Carolina, Fair, Damien A, Dick, Anthony Steven, Sutherland, Matthew T, Casey, BJ, Barch, Deanna M, Harms, Michael P, Watts, Richard, Bjork, James M, Garavan, Hugh P, Hilmer, Laura, Pung, Christopher J, Sicat, Chelsea S, Kuperman, Joshua, Bartsch, Hauke, Xue, Feng, Heitzeg, Mary M, Laird, Angela R, Trinh, Thanh T, Gonzalez, Raul, Tapert, Susan F, Riedel, Michael C, Squeglia, Lindsay M, Hyde, Luke W, Rosenberg, Monica D, Earl, Eric A, Howlett, Katia D, Baker, Fiona C, Soules, Mary, Diaz, Jazmin, de Leon, Octavio Ruiz, Thompson, Wesley K, Neale, Michael C, Herting, Megan, Sowell, Elizabeth R, Alvarez, Ruben P, Hawes, Samuel W, Sanchez, Mariana, Bodurka, Jerzy, Breslin, Florence J, Morris, Amanda Sheffield, Paulus, Martin P, Simmons, W Kyle, Polimeni, Jonathan R, van der Kouwe, Andre, Nencka, Andrew S, Gray, Kevin M, Pierpaoli, Carlo, Matochik, John A, Noronha, Antonio, Aklin, Will M, Conway, Kevin, Glantz, Meyer, Hoffman, Elizabeth, Little, Roger, Lopez, Marsha, Pariyadath, Vani, Weiss, Susan RB, Wolff-Hughes, Dana L, DelCarmen-Wiggins, Rebecca, Ewing, Sarah W Feldstein, Miranda-Dominguez, Oscar, Nagel, Bonnie J, Perrone, Anders J, Sturgeon, Darrick T, Goldstone, Aimee, Pfefferbaum, Adolf, Pohl, Kilian M, Prouty, Devin, Uban, Kristina, Bookheimer, Susan Y, Dapretto, Mirella, Galvan, Adriana, Bagot, Kara, Giedd, Jay, Infante, M Alejandra, Jacobus, Joanna, Patrick, Kevin, Shilling, Paul D, Desikan, Rahul, Li, Yi, Sugrue, Leo, Banich, Marie T, Friedman, Naomi, Hewitt, John K, Hopfer, Christian, Sakai, Joseph, Tanabe, Jody, Cottler, Linda B, Nixon, Sara Jo, Chang, Linda, Cloak, Christine, Ernst, Thomas, Reeves, Gloria, Kennedy, David N, Heeringa, Steve, and Peltier, Scott
- Subjects
Biomedical and Clinical Sciences ,Health Sciences ,Brain Disorders ,Mental Illness ,Mental Health ,Clinical Research ,Pediatric ,Drug Abuse (NIDA only) ,Biomedical Imaging ,Basic Behavioral and Social Science ,Substance Misuse ,Neurosciences ,Women's Health ,Behavioral and Social Science ,Mental health ,Neurological ,Good Health and Well Being ,Adolescent ,Adolescent Development ,Brain ,Brain Mapping ,Diffusion Magnetic Resonance Imaging ,Humans ,Image Processing ,Computer-Assisted ,Magnetic Resonance Imaging ,Multimodal Imaging ,Signal Processing ,Computer-Assisted ,Magnetic resonance imaging ,ABCD ,Data sharing ,Processing pipeline ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Neurology & Neurosurgery ,Biomedical and clinical sciences ,Health sciences - Abstract
The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.
- Published
- 2019
4. Image processing and analysis methods for the Adolescent Brain Cognitive Development Study
- Author
-
Hagler, Donald J., Jr., Hatton, SeanN., Cornejo, M. Daniela, Makowski, Carolina, Fair, Damien A., Dick, Anthony Steven, Sutherland, Matthew T., Casey, B.J., Barch, Deanna M., Harms, Michael P., Watts, Richard, Bjork, James M., Garavan, Hugh P., Hilmer, Laura, Pung, Christopher J., Sicat, Chelsea S., Kuperman, Joshua, Bartsch, Hauke, Xue, Feng, Heitzeg, Mary M., Laird, Angela R., Trinh, Thanh T., Gonzalez, Raul, Tapert, Susan F., Riedel, Michael C., Squeglia, Lindsay M., Hyde, Luke W., Rosenberg, Monica D., Earl, Eric A., Howlett, Katia D., Baker, Fiona C., Soules, Mary, Diaz, Jazmin, de Leon, Octavio Ruiz, Thompson, Wesley K., Neale, Michael C., Herting, Megan, Sowell, Elizabeth R., Alvarez, Ruben P., Hawes, Samuel W., Sanchez, Mariana, Bodurka, Jerzy, Breslin, Florence J., Morris, Amanda Sheffield, Paulus, Martin P., Simmons, W. Kyle, Polimeni, Jonathan R., van der Kouwe, Andre, Nencka, Andrew S., Gray, Kevin M., Pierpaoli, Carlo, Matochik, John A., Noronha, Antonio, Aklin, Will M., Conway, Kevin, Glantz, Meyer, Hoffman, Elizabeth, Little, Roger, Lopez, Marsha, Pariyadath, Vani, Weiss, Susan RB., Wolff-Hughes, Dana L., DelCarmen-Wiggins, Rebecca, Feldstein Ewing, Sarah W., Miranda-Dominguez, Oscar, Nagel, Bonnie J., Perrone, Anders J., Sturgeon, Darrick T., Goldstone, Aimee, Pfefferbaum, Adolf, Pohl, Kilian M., Prouty, Devin, Uban, Kristina, Bookheimer, Susan Y., Dapretto, Mirella, Galvan, Adriana, Bagot, Kara, Giedd, Jay, Infante, M. Alejandra, Jacobus, Joanna, Patrick, Kevin, Shilling, Paul D., Desikan, Rahul, Li, Yi, Sugrue, Leo, Banich, Marie T., Friedman, Naomi, Hewitt, John K., Hopfer, Christian, Sakai, Joseph, Tanabe, Jody, Cottler, Linda B., Nixon, Sara Jo, Chang, Linda, Cloak, Christine, Ernst, Thomas, Reeves, Gloria, Kennedy, David N., Heeringa, Steve, Peltier, Scott, Schulenberg, John, Sripada, Chandra, Zucker, Robert A., Iacono, William G., Luciana, Monica, Calabro, Finnegan J., Clark, Duncan B., Lewis, David A., Luna, Beatriz, Schirda, Claudiu, Brima, Tufikameni, Foxe, John J., Freedman, Edward G., Mruzek, Daniel W., Mason, Michael J., Huber, Rebekah, McGlade, Erin, Prescot, Andrew, Renshaw, Perry F., Yurgelun-Todd, Deborah A., Allgaier, Nicholas A., Dumas, Julie A., Ivanova, Masha, Potter, Alexandra, Florsheim, Paul, Larson, Christine, Lisdahl, Krista, Charness, Michael E., Fuemmeler, Bernard, Hettema, John M., Maes, Hermine H., Steinberg, Joel, Anokhin, Andrey P., Glaser, Paul, Heath, Andrew C., Madden, Pamela A., Baskin-Sommers, Arielle, Constable, R. Todd, Grant, Steven J., Dowling, Gayathri J., Brown, Sandra A., Jernigan, Terry L., and Dale, Anders M.
- Published
- 2019
- Full Text
- View/download PDF
5. Multiple Imputation with Massive Data: An Application to the Panel Study of Income Dynamics.
- Author
-
Si, Yajuan, Heeringa, Steve, Johnson, David, Little, Roderick J A, Liu, Wenshuo, Pfeffer, Fabian, and Raghunathan, Trivellore
- Subjects
- *
PANEL analysis , *INCOME , *MISSING data (Statistics) , *NET worth , *HOUSEHOLD surveys , *HOUSEKEEPING - Abstract
Multiple imputation (MI) is a popular and well-established method for handling missing data in multivariate data sets, but its practicality for use in massive and complex data sets has been questioned. One such data set is the Panel Study of Income Dynamics (PSID), a longstanding and extensive survey of household income and wealth in the United States. Missing data for this survey are currently handled using traditional hot deck methods because of the simple implementation; however, the univariate hot deck results in large random wealth fluctuations. MI is effective but faced with operational challenges. We use a sequential regression/chained-equation approach, using the software IVEware, to multiply impute cross-sectional wealth data in the 2013 PSID, and compare analyses of the resulting imputed data with those from the current hot deck approach. Practical difficulties, such as non-normally distributed variables, skip patterns, categorical variables with many levels, and multicollinearity, are described together with our approaches to overcoming them. We evaluate the imputation quality and validity with internal diagnostics and external benchmarking data. MI produces improvements over the existing hot deck approach by helping preserve correlation structures, such as the associations between PSID wealth components and the relationships between the household net worth and sociodemographic factors, and facilitates completed data analyses with general purposes. MI incorporates highly predictive covariates into imputation models and increases efficiency. We recommend the practical implementation of MI and expect greater gains when the fraction of missing information is large. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
6. Multiple Imputation with Massive Data: An Application to the Panel Study of Income Dynamics
- Author
-
Si, Yajuan, primary, Heeringa, Steve, additional, Johnson, David, additional, Little, Roderick J A, additional, Liu, Wenshuo, additional, Pfeffer, Fabian, additional, and Raghunathan, Trivellore, additional
- Published
- 2021
- Full Text
- View/download PDF
7. Recent developments of sampling hard-to-survey populations: an assessment
- Author
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Lee, Sunghee, primary, Wagner, James, additional, Valliant, Richard, additional, and Heeringa, Steve, additional
- Published
- 2014
- Full Text
- View/download PDF
8. Image processing and analysis methods for the Adolescent Brain Cognitive Development Study.
- Author
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Cornejo, M, Cornejo, M, Makowski, Carolina, Fair, Damien, Dick, Anthony, Sutherland, Matthew, Casey, B, Barch, Deanna, Harms, Michael, Watts, Richard, Bjork, James, Garavan, Hugh, Hilmer, Laura, Pung, Christopher, Sicat, Chelsea, Kuperman, Joshua, Bartsch, Hauke, Xue, Feng, Heitzeg, Mary, Laird, Angela, Trinh, Thanh, Gonzalez, Raul, Neale, Michael, Herting, Megan, Sowell, Elizabeth, Alvarez, Ruben, Hawes, Samuel, Sanchez, Mariana, Bodurka, Jerzy, Breslin, Florence, Morris, Amanda, Paulus, Martin, Simmons, W, Polimeni, Jonathan, van der Kouwe, Andre, Nencka, Andrew, Gray, Kevin, Pierpaoli, Carlo, Matochik, John, Noronha, Antonio, Aklin, Will, Conway, Kevin, Glantz, Meyer, Hoffman, Elizabeth, Little, Roger, Lopez, Marsha, Pariyadath, Vani, Weiss, Susan, Wolff-Hughes, Dana, DelCarmen-Wiggins, Rebecca, Feldstein Ewing, Sarah, Miranda-Dominguez, Oscar, Nagel, Bonnie, Perrone, Anders, Sturgeon, Darrick, Goldstone, Aimee, Pfefferbaum, Adolf, Pohl, Kilian, Prouty, Devin, Shilling, Paul, Desikan, Rahul, Li, Yi, Sugrue, Leo, Banich, Marie, Friedman, Naomi, Hewitt, John, Hopfer, Christian, Sakai, Joseph, Tanabe, Jody, Cottler, Linda, Nixon, Sara, Chang, Linda, Cloak, Christine, Ernst, Thomas, Reeves, Gloria, Kennedy, David, Heeringa, Steve, Peltier, Scott, Schulenberg, John, Sripada, Chandra, Zucker, Robert, Iacono, William, Luciana, Monica, Calabro, Finnegan, Clark, Duncan, Lewis, David, Luna, Beatriz, Schirda, Claudiu, Brima, Tufikameni, Foxe, John, Freedman, Edward, Mruzek, Daniel, Mason, Michael, Huber, Rebekah, McGlade, Erin, Prescot, Andrew, Renshaw, Perry, Riedel, Michael, Squeglia, Lindsay, Hyde, Luke, Rosenberg, Monica, Cornejo, M, Cornejo, M, Makowski, Carolina, Fair, Damien, Dick, Anthony, Sutherland, Matthew, Casey, B, Barch, Deanna, Harms, Michael, Watts, Richard, Bjork, James, Garavan, Hugh, Hilmer, Laura, Pung, Christopher, Sicat, Chelsea, Kuperman, Joshua, Bartsch, Hauke, Xue, Feng, Heitzeg, Mary, Laird, Angela, Trinh, Thanh, Gonzalez, Raul, Neale, Michael, Herting, Megan, Sowell, Elizabeth, Alvarez, Ruben, Hawes, Samuel, Sanchez, Mariana, Bodurka, Jerzy, Breslin, Florence, Morris, Amanda, Paulus, Martin, Simmons, W, Polimeni, Jonathan, van der Kouwe, Andre, Nencka, Andrew, Gray, Kevin, Pierpaoli, Carlo, Matochik, John, Noronha, Antonio, Aklin, Will, Conway, Kevin, Glantz, Meyer, Hoffman, Elizabeth, Little, Roger, Lopez, Marsha, Pariyadath, Vani, Weiss, Susan, Wolff-Hughes, Dana, DelCarmen-Wiggins, Rebecca, Feldstein Ewing, Sarah, Miranda-Dominguez, Oscar, Nagel, Bonnie, Perrone, Anders, Sturgeon, Darrick, Goldstone, Aimee, Pfefferbaum, Adolf, Pohl, Kilian, Prouty, Devin, Shilling, Paul, Desikan, Rahul, Li, Yi, Sugrue, Leo, Banich, Marie, Friedman, Naomi, Hewitt, John, Hopfer, Christian, Sakai, Joseph, Tanabe, Jody, Cottler, Linda, Nixon, Sara, Chang, Linda, Cloak, Christine, Ernst, Thomas, Reeves, Gloria, Kennedy, David, Heeringa, Steve, Peltier, Scott, Schulenberg, John, Sripada, Chandra, Zucker, Robert, Iacono, William, Luciana, Monica, Calabro, Finnegan, Clark, Duncan, Lewis, David, Luna, Beatriz, Schirda, Claudiu, Brima, Tufikameni, Foxe, John, Freedman, Edward, Mruzek, Daniel, Mason, Michael, Huber, Rebekah, McGlade, Erin, Prescot, Andrew, Renshaw, Perry, Riedel, Michael, Squeglia, Lindsay, Hyde, Luke, and Rosenberg, Monica
- Abstract
The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.
- Published
- 2019
9. Use of Multiple Imputation to Correct for Nonresponse Bias in a Survey of Urologic Symptoms among African-American Men
- Author
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Taylor, Jeremy M. G., Cooper, Kristine L., Wei, John T., Sarma, Aruna V., Raghunathan, Trivellore E., and Heeringa, Steve G.
- Published
- 2002
10. Image processing and analysis methods for the Adolescent Brain Cognitive Development Study
- Author
-
Hagler, Donald J, primary, Hatton, Sean N, additional, Makowski, Carolina, additional, Cornejo, M Daniela, additional, Fair, Damien A, additional, Dick, Anthony Steven, additional, Sutherland, Matthew T, additional, Casey, BJ, additional, Barch, Deanna M, additional, Harms, Michael P, additional, Watts, Richard, additional, Bjork, James M, additional, Garavan, Hugh P, additional, Hilmer, Laura, additional, Pung, Christopher J, additional, Sicat, Chelsea S, additional, Kuperman, Joshua, additional, Bartsch, Hauke, additional, Xue, Feng, additional, Heitzeg, Mary M, additional, Laird, Angela R, additional, Trinh, Thanh T, additional, Gonzalez, Raul, additional, Tapert, Susan F, additional, Riedel, Michael C, additional, Squeglia, Lindsay M, additional, Hyde, Luke W, additional, Rosenberg, Monica D, additional, Earl, Eric A, additional, Howlett, Katia D, additional, Baker, Fiona C, additional, Soules, Mary, additional, Diaz, Jazmin, additional, Leon, Octavio Ruiz de, additional, Thompson, Wesley K, additional, Neale, Michael C, additional, Herting, Megan, additional, Sowell, Elizabeth R, additional, Alvarez, Ruben P, additional, Hawes, Samuel W, additional, Sanchez, Mariana, additional, Bodurka, Jerzy, additional, Breslin, Florence J, additional, Morris, Amanda Sheffield, additional, Paulus, Martin P, additional, Simmons, W Kyle, additional, Polimeni, Jonathan R, additional, Kouwe, Andre van der, additional, Nencka, Andrew S, additional, Gray, Kevin M, additional, Pierpaoli, Carlo, additional, Matochik, John A, additional, Noronha, Antonio, additional, Aklin, Will M, additional, Conway, Kevin, additional, Glantz, Meyer, additional, Hoffman, Elizabeth, additional, Little, Roger, additional, Lopez, Marsha, additional, Pariyadath, Vani, additional, Weiss, Susan RB, additional, Wolff-Hughes, Dana L, additional, DelCarmen-Wiggins, Rebecca, additional, Ewing, Sarah W Feldstein, additional, Miranda-Dominguez, Oscar, additional, Nagel, Bonnie J, additional, Perrone, Anders J, additional, Sturgeon, Darrick T, additional, Goldstone, Aimee, additional, Pfefferbaum, Adolf, additional, Pohl, Kilian M, additional, Prouty, Devin, additional, Uban, Kristina, additional, Bookheimer, Susan Y, additional, Dapretto, Mirella, additional, Galvan, Adriana, additional, Bagot, Kara, additional, Giedd, Jay, additional, Infante, M Alejandra, additional, Jacobus, Joanna, additional, Patrick, Kevin, additional, Shilling, Paul D, additional, Desikan, Rahul, additional, Li, Yi, additional, Sugrue, Leo, additional, Banich, Marie T, additional, Friedman, Naomi, additional, Hewitt, John K, additional, Hopfer, Christian, additional, Sakai, Joseph, additional, Tanabe, Jody, additional, Cottler, Linda B, additional, Nixon, Sara Jo, additional, Chang, Linda, additional, Cloak, Christine, additional, Ernst, Thomas, additional, Reeves, Gloria, additional, Kennedy, David N, additional, Heeringa, Steve, additional, Peltier, Scott, additional, Schulenberg, John, additional, Sripada, Chandra, additional, Zucker, Robert A, additional, Iacono, William G, additional, Luciana, Monica, additional, Calabro, Finnegan J, additional, Clark, Duncan B, additional, Lewis, David A, additional, Luna, Beatriz, additional, Schirda, Claudiu, additional, Brima, Tufikameni, additional, Foxe, John J, additional, Freedman, Edward G, additional, Mruzek, Daniel W, additional, Mason, Michael J, additional, Huber, Rebekah, additional, McGlade, Erin, additional, Prescot, Andrew, additional, Renshaw, Perry F, additional, Yurgelun-Todd, Deborah A, additional, Allgaier, Nicholas A, additional, Dumas, Julie A, additional, Ivanova, Masha, additional, Potter, Alexandra, additional, Florsheim, Paul, additional, Larson, Christine, additional, Lisdahl, Krista, additional, Charness, Michael E, additional, Fuemmeler, Bernard, additional, Hettema, John M, additional, Steinberg, Joel, additional, Anokhin, Andrey P, additional, Glaser, Paul, additional, Heath, Andrew C, additional, Madden, Pamela A, additional, Baskin-Sommers, Arielle, additional, Constable, R Todd, additional, Grant, Steven J, additional, Dowling, Gayathri J, additional, Brown, Sandra A, additional, Jernigan, Terry L, additional, and Dale, Anders M, additional
- Published
- 2018
- Full Text
- View/download PDF
11. Mexican Americans Participate in Research More than Expected while non-Hispanic Whites Participate Less than Expected
- Author
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Gonzales, Xavier F., Heeringa, Steven G., Briceño, Emily M., Mehdipanah, Roshanak, Levine, Deborah A., Langa, Kenneth M., Garcia, Nelda, Longoria, Ruth, and Morgenstern, Lewis B.
- Published
- 2022
- Full Text
- View/download PDF
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