[et_pb_section bb_built=”1″ background_color=”#f7f7f7″ _builder_version=”3.0.78″ module_class=”first-content”][et_pb_row _builder_version=”3.0.78″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” _i=”0″ _address=”1.0″][et_pb_column type=”4_4″][et_pb_text _builder_version=”3.0.78″ background_color=”#f7f7f7″ background_layout=”light” border_style=”solid” text_orientation=”center” module_alignment=”center”]<\/p>\n
[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section bb_built=”1″ module_class=”volle-breite same-height column-50 height-image” _builder_version=”3.0.78″ custom_padding=”0px||0px|0px”][et_pb_row make_fullwidth=”on” custom_padding=”0px|0px|0px|0px” background_color_2=”#ffffff” padding_top_2=”0px” padding_right_2=”0px” padding_bottom_2=”0px” padding_left_2=”0px” _builder_version=”3.0.78″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” module_class_2=”abstand”][et_pb_column type=”1_2″][et_pb_image _builder_version=”3.0.78″ src=”https:\/\/dpc-software.de\/wp-content\/uploads\/2017\/10\/dpc-software.jpg” show_in_lightbox=”off” url_new_window=”off” use_overlay=”off” always_center_on_mobile=”on” border_style=”solid” force_fullwidth=”off” show_bottom_space=”on” \/][\/et_pb_column][et_pb_column type=”1_2″][et_pb_text _builder_version=”3.0.78″ background_color=”#ffffff” background_layout=”light” border_style=”solid”]<\/p>\n
Lineare Modelle<\/a> Longitudinal-\/Paneldaten<\/a> Modelle mit mehrstufigen gemischten Effekten<\/a> Z\u00e4hldaten, bin\u00e4re und beschr\u00e4nkte (limited) Zielgr\u00f6\u00dfen<\/a> Verallgemeinerte Lineare Modelle<\/a> ANOVA\/MANOVA<\/a> Exakte Statistik<\/a> Tests, Prognosen und Effekte<\/a> Kontraste, paarweise Vergleiche und Margins<\/a> GMM und nicht-lineare Regression<\/a> [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section bb_built=”1″ module_class=”volle-breite abstand same-height column-50 kontakt” _builder_version=”3.0.78″ custom_padding=”0px||0px|0px”][et_pb_row make_fullwidth=”on” custom_padding=”0px|0px|0px|0px” background_color_2=”#ffffff” padding_top_2=”0px” padding_right_2=”0px” padding_bottom_2=”0px” padding_left_2=”0px” module_class_2=”grau” _builder_version=”3.0.78″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” module_class_1=”text-unserteam”][et_pb_column type=”1_2″][et_pb_text _builder_version=”3.0.78″ background_layout=”light” border_style=”solid”]<\/p>\n Survival-Analyse<\/a> Bayessche Analyse<\/a> Testst\u00e4rke und Stichprobenumfang<\/a> Treatment-Effekte<\/a> Strukturgleichungsmodelle (SEM)<\/a> Multiple Imputation<\/a> Survey-Methoden<\/a> Cluster-Analyse<\/a> Probabilistische Testtheorie (Item Response Theory, IRT)<\/a> Multivariate Methoden<\/a> Nicht-parametrische Methoden<\/a> Epidemiologische Verfahren<\/a> Datanmanagement<\/a> [\/et_pb_text][\/et_pb_column][et_pb_column type=”1_2″][et_pb_text _builder_version=”3.0.78″ background_layout=”light” border_style=”solid”]<\/p>\n Grafiken<\/a> Benutzeroberfl\u00e4che<\/a> Maximum Likelihood<\/a> Programmierbares Maximum Likelihood<\/a> Resampling und Simulationsmethoden<\/a> Zeitreihen<\/a> Dokumentation<\/a> Basistatistiken<\/a> Weitere statistische Methoden<\/a> Funktionen<\/a> Internet-Optionen<\/a> User-Programme<\/a> Programmierung<\/a> Matrix-Programmierung – MATA<\/a> Integrierte L\u00f6sungen<\/a> Installationsqualifizierung<\/a> Barrierefreiheit<\/a> Beispiel-Session [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section bb_built=”1″ background_color=”#e2001a” _builder_version=”3.0.78″ custom_padding=”54px|0px|52px|0px” module_class=”abschluss”][et_pb_row _builder_version=”3.0.78″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” _i=”0″ _address=”4.0″][et_pb_column type=”4_4″][et_pb_text _builder_version=”3.0.78″ background_layout=”dark” border_style=”solid” text_orientation=”center” module_alignment=”center”]<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”3.0.78″][et_pb_column type=”1_3″][et_pb_text _builder_version=”3.0.78″ background_layout=”light” border_style=”solid”]<\/p>\n Ihre Ansprechpartner [\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″][et_pb_text _builder_version=”3.0.78″]<\/p>\n Ihr Ansprechpartner [\/et_pb_text][\/et_pb_column][et_pb_column type=”1_3″][et_pb_text _builder_version=”3.0.78″]<\/p>\n Allgemeine Fragen<\/b> [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"
\nregression | censored outcomes | endogenous regressors | bootstrap, jackknife, and robust and cluster-robust variance |
\ninstrumental variables | three-stage least squares | constraints | quantile regression | GLS<\/p>\n
\nrandom and fixed effects with robust standard errors | linear mixed models | random-effects probit | GEE |
\nrandom- and fixed-effects Poisson | dynamic panel-data models | instrumental variables | panel unit-root tests<\/p>\n
\ncontinuous, binary, count, and survival outcomes | two-, three-, and higher-level models | generalized linear models | random-intercepts | random-slopes | crossed random effects | BLUPs of effects and fitted values | hierarchical models | residual error structures | DDF adjustments | support for survey data<\/p>\n
\nlogistic, probit, tobit | Poisson and negative binomial | conditional, multinomial, nested, ordered, rank-ordered, and stereotype logistic | multinomial probit | zero-inflated and left-truncated count models | selection models | marginal effects<\/p>\n
\nten link functions | user-defined links | seven distributions | ML and IRLS estimation | nine variance estimators | seven residuals<\/p>\n
\nbalanced and unbalanced designs | factorial, nested, and mixed designs | repeated measures | marginal means | contrasts<\/p>\n
\nexact logistic and Poisson regression | exact case-control statistics | binomial tests | Fisher’s exact test for r x c tables<\/p>\n
\nWald tests | LR tests | linear and nonlinear combinations | predictions and generalized predictions | marginal means | least-squares means | adjusted means | marginal and partial effects | forecast models | Hausman tests<\/p>\n
\ncompare means, intercepts, or slopes | compare to reference category, adjacent category, grand mean, etc. | orthogonal polynomials | multiple-comparison adjustments | graph estimated means and contrasts | interaction plots<\/p>\n
\ngeneralized method of moments (GMM) | nonlinear regression<\/p>\n
\nKaplan-Meier and Nelson-Aalen estimators | Cox regression (frailty) | parametric models (frailty, random effects) | competing risks | hazards | time-varying covariates | left- and right-censoring, Weibull, exponential, and Gompertz models<\/p>\n
\nthousands of built-in models | univariate and multivariate models | linear and nonlinear models | continuous, binary, ordinal, and count outcomes | continuous univariate, multivariate, and discrete priors | add your own models | adaptive Metropolis-Hastings sampling | Gibbs sampling | convergence diagnostics | posterior summaries | hypothesis testing | model comparison<\/p>\n
\npower | sample size | effect size | minimum detectable effect | means | proportions | variances | correlations | ANOVA | case-control studies | cohort studies | contingency tables | survival analysis | balanced or unbalanced designs | results in tables or graphs<\/p>\n
\ninverse probability weight (IPW) | doubly robust methods | propensity score matching | regression adjustment | covariate matching | multilevel treatments | endogenous treatments | average treatment effects (ATEs) | ATEs on the treated (ATETs) | potential-outcome means (POMs) | continuous, binary, count, fractional, and survival outcomes<\/p>\n
\ngraphical path diagram builder | standardized and unstandardized estimates | modification indices | direct and indirect effects | continuous, binary, count, ordinal, and survival outcomes | multilevel models | random slopes and intercepts | factors scores, empirical Bayes, and other predictions | groups and tests of invariance | goodness of fit | handles MAR data by FIML | correlated data | survey data<\/p>\n
\nnine univariate imputation methods | multivariate normal imputation | chained equations | explore pattern of missingness | manage imputed datasets | fit model and pool results | transform parameters | joint tests of parameter estimates | predictions<\/p>\n
\nmultistage designs | bootstrap, BRR, jackknife, linearized, and SDR variance estimation | poststratification | DEFF | predictive margins | means, proportions, ratios, totals | summary tables | regression, instrumental variables, probit, Cox regression<\/p>\n
\nhierarchical clustering | kmeans and kmedian nonhierarchical clustering | dendrograms | stopping rules | user-extensible analyses<\/p>\n
\nbinary (1PL, 2PL, 3PL), ordinal, and categorical response models | item characteristic curves | test characteristic curves | item information functions | test information functions | differential item functioning (DIF)<\/p>\n
\nfactor analysis | principal components | discriminant analysis | rotation | multidimensional scaling | Procrustean analysis | correspondence analysis | biplots | dendrograms | user-extensible analyses<\/p>\n
\nWilcoxon-Mann-Whitney, Wilcoxon signed ranks, and Kruskal-Wallis tests | Spearman and Kendall correlations | Kolmogorov-Smirnov tests | exact binomial CIs | survival data | ROC analysis | smoothing | bootstrapping<\/p>\n
\nstandardization of rates | case-control | cohort | matched case-control | Mantel-Haenszel | pharmacokinetics | ROC analysis | ICD-10<\/p>\n
\ndata transformations | match-merge | import\/export data | ODBC | SQL | XML | by-group processing | append files | sort | row-column transposition | labeling | saving results<\/p>\n
\nline charts | scatterplots | bar charts | pie charts | hi-lo charts | contour plots | GUI Editor | regression diagnostic graphs | survival plots | nonparametric smoothers | distribution Q-Q plots<\/p>\n
\nmenus and dialogs for all features | Data Editor | Variables Manager | Graph Editor | Project Manager | Do-file Editor | Clipboard Preview Tool | multiple preference sets<\/p>\n
\nspecify likelihood using simple expressions | no programming required | survey data | standard, robust, bootstrap, and jackknife SEs | matrix estimators<\/p>\n
\nuser-specified functions | NR, DFP, BFGS, BHHH | OIM, OPG, robust, bootstrap, and jackknife SEs | Wald tests | survey data | numeric or analytic derivatives<\/p>\n
\nbootstrap | jackknife | Monte Carlo simulation | permutation tests<\/p>\n
\nARIMA | ARFIMA | ARCH\/GARCH | VAR | VECM | multivariate GARCH | unobserved-components model | dynamic factors | state-space models | Markov-switching models | business calendars | correlograms | periodograms | forecasts | impulse-response functions | unit-root tests | filters and smoothers | rolling and recursive estimation<\/p>\n
\n27 manuals | 14,000+ pages | seamless navigation | thousands of worked examples | quick starts | methods and formulas | references<\/p>\n
\nsummaries | cross-tabulations | correlations | z and t tests | equality-of-variance tests | tests of proportions | confidence intervals | factor variables<\/p>\n
\nkappa measure of interrater agreement | Cronbach’s alpha | stepwise regression | tests of normality<\/p>\n
\nstatistical | random-number | mathematical | string | date and time<\/p>\n
\nability to install new commands | web updating | web file sharing | latest Stata news<\/p>\n
\nuser-written commands for meta-analysis, data management, survival, econometrics<\/p>\n
\nadding new commands | command scripting | object-oriented programming | menu and dialog-box programming | Project Manager | plugins<\/p>\n
\ninteractive sessions | large-scale development projects | optimization | matrix inversions | decompositions | eigenvalues and eigenvectors | LAPACK engine | real and complex numbers | string matrices | interface to Stata datasets and matrices | numerical derivatives | object-oriented programming<\/p>\n
\nNumerics by Stata<\/p>\n
\nIQ report for regulatory agencies such as the FDA | installation verification<\/p>\n
\nSection 508 compliance, accessibility for persons with disabilities<\/p>\n
\nA sample session of Stata for Mac<\/a>, Unix<\/a>, or Windows<\/a><\/p>\nIhre Ansprechpartner<\/h2>\n
\nf\u00fcr Versicherungsthemen, APL und Projekte<\/b>
\nAxel Holzm\u00fcller<\/a>
\nAlp Atayalp<\/a>
\nTel\u00a0(0)212 \/ 2 60 66-50<\/a><\/p>\n
\nf\u00fcr Enterprise Software<\/b>
\nAlp Atayalp<\/a>
\nTel (0)212 \/ 2 60 66-26<\/a><\/p>\n
\nrichten Sie bitte an
\nprojekte@dpc-software.de<\/a>
\nTel (0)212 \/ 2 60 66-0<\/a>
\nfax +49 (0)212 \/ 2 60 66-66<\/p>\n