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Advances in data analysis for prevention intervention research.
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  • Advances in data analysis for prevention intervention research.
Utgivning, distribution etc.
  • National Institute on Drug Abuse, Rockville, Md : 1994
Fysisk beskrivning
  • 456 s : ill.
Serietitel - biuppslagsform
  • NIDA research monograph series ; 142
  • NIH publication ; 94-3599
Anmärkning: Allmän
  • E-bok
Anmärkning: Innehållsbeskrivning, sammanfattning
  • New statitical methods for substance use prevention research. Analysis with missing data in drug prevention research. Latent class analysis of substance abuse patterns. Latent transition analysis and how it can address prevention research questions. Incorporating trend data to aid in the causal interpretation of individual-level correlations among variables: examples focusing on the recent decline in marijuana use. Multilevel models for hierarchically nested data: potential applications in substance abuse prevention research. Seven ways to increase power without increasing N. Designing and analyzing studies of onset, cessation, and relapse: using survival analysis in drug abuse prevention research. Time series models of individual substance abusers. Use and misuse of repeated measures designs . Meta-analytical issues for prevention intervention research. Dynamic systems-modeling as a means to estimate community-based prevention effects.
Term
Indexterm - Okontrollerad
Personnamn
Institutionsnamn
  • National Institute on Drug Abuse 
*000      am a        a
*00117182
*007cr |||||||||||
*008070120s1994||||xxu||||es|||||||||1|eng||
*24510$aAdvances in data analysis for prevention intervention research.
*260  $aRockville, Md :$bNational Institute on Drug Abuse,$c1994
*300  $a456 s :$bill.
*440  $aNIDA research monograph series ;$v142
*440  $aNIH publication ;$v94-3599
*500  $aE-bok
*520  $aNew statitical methods for substance use prevention research. Analysis with missing data in drug prevention research. Latent class analysis of substance abuse patterns. Latent transition analysis and how it can address prevention research questions. Incorporating trend data to aid in the causal interpretation of individual-level correlations among variables: examples focusing on the recent decline in marijuana use. Multilevel models for hierarchically nested data: potential applications in substance abuse prevention research. Seven ways to increase power without increasing N. Designing and analyzing studies of onset, cessation, and relapse: using survival analysis in drug abuse prevention research. Time series models of individual substance abusers. Use and misuse of repeated measures designs . Meta-analytical issues for prevention intervention research. Dynamic systems-modeling as a means to estimate community-based prevention effects.
*650 4$aPrevention
*650 4$aResearch
*650 4$aSubstance abuse
*650 4$aMarijuana smoking
*650 4$aModels, statistical
*650 4$aStatistics
*650 4$aMethods
*650 4$aData interpretation, statistical
*650 4$aSurvival analysis
*650 4$aMeta-analysis
*653  $aStatistik
*653  $aMetoder
*653  $aDrogmissbruk
*7001 $aCollins, Linda M.$eed.
*7001 $aSeitz, Larry A.$eed.
*7101 $aNational Institute on Drug Abuse$0124050
*85640$uhttps://archives.drugabuse.gov/sites/default/files/monograph142.pdf
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