structure(list(Estimate = c(-0.006, 0.005, 0.027, 0.122, 0.118, 
0.193, 0.322, 0.347, 0.403, 0.493, 0.574, 0.605, 0.61, 0.583, 
0.523, 0.515, 0.479, 0.451, 0.428, 0.431, 0.405, 0.405, 0.381, 
0.346, 0.343, 0.365, 0.363, 0.413, 0.422, 0.41, 0.319, 0.285, 
0.27, 0.272, 0.312, 0.343, 0.255, 0.215, 0.195, 0.217, 0.246, 
0.276, 0.312, 0.298, 0.314, 0.289, 0.307, 0.309, 0.26, 0.301, 
0.32, 0.378, 0.373, 0.24, 0.246), StdErr = c(0.08, 0.08, 0.078, 
0.101, 0.113, 0.122, 0.124, 0.115, 0.108, 0.091, 0.089, 0.093, 
0.09, 0.095, 0.085, 0.09, 0.098, 0.108, 0.107, 0.108, 0.108, 
0.11, 0.112, 0.113, 0.11, 0.116, 0.103, 0.098, 0.106, 0.103, 
0.108, 0.108, 0.106, 0.114, 0.113, 0.116, 0.109, 0.099, 0.102, 
0.109, 0.111, 0.104, 0.097, 0.099, 0.095, 0.092, 0.091, 0.091, 
0.108, 0.116, 0.112, 0.121, 0.125, 0.126, 0.129), Statistic = c(-0.081, 
0.068, 0.365, 1.272, 1.098, 1.669, 2.725, 3.177, 3.905, 5.645, 
6.732, 6.838, 7.079, 6.422, 6.473, 6.002, 5.137, 4.371, 4.18, 
4.193, 3.912, 3.891, 3.564, 3.223, 3.262, 3.302, 3.684, 4.405, 
4.19, 4.173, 3.106, 2.772, 2.675, 2.514, 2.908, 3.105, 2.461, 
2.27, 2.013, 2.1, 2.327, 2.794, 3.396, 3.17, 3.446, 3.299, 3.54, 
3.56, 2.522, 2.722, 2.996, 3.296, 3.142, 2.015, 2.006), Prob = c(0.936, 
0.947, 0.718, 0.215, 0.283, 0.108, 0.012, 0.004, 0.001, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.001, 0.001, 0.001, 0.003, 0.003, 
0.003, 0.001, 0, 0, 0, 0.005, 0.01, 0.013, 0.019, 0.008, 0.005, 
0.021, 0.032, 0.055, 0.046, 0.028, 0.01, 0.002, 0.004, 0.002, 
0.003, 0.002, 0.001, 0.018, 0.012, 0.006, 0.003, 0.005, 0.055, 
0.056), DF = c(25, 25, 25, 25, 25, 25, 25, 26, 26, 26, 26, 26, 
26, 26, 26, 26, 26, 26, 26, 26, 26, 25, 26, 26, 26, 25, 26, 26, 
26, 26, 26, 26, 25, 24, 25, 26, 26, 26, 26, 25, 25, 25, 25, 26, 
26, 26, 26, 26, 26, 25, 24, 22, 23, 24, 24), Time = c(15500, 
15600, 15700, 15800, 15900, 16000, 16100, 16200, 16300, 16400, 
16500, 16600, 16700, 16800, 16900, 17000, 17100, 17200, 17300, 
17400, 17500, 17600, 17700, 17800, 17900, 18000, 18100, 18200, 
18300, 18400, 18500, 18600, 18700, 18800, 18900, 19000, 19100, 
19200, 19300, 19400, 19500, 19600, 19700, 19800, 19900, 20000, 
20100, 20200, 20300, 20400, 20500, 20600, 20700, 20800, 20900
), CritStatisticPos = c(3.763, 3.763, 3.763, 3.763, 3.763, 3.763, 
3.763, 3.744, 3.744, 3.744, 3.744, 3.744, 3.744, 3.744, 3.744, 
3.744, 3.744, 3.744, 3.744, 3.744, 3.744, 3.763, 3.744, 3.744, 
3.744, 3.763, 3.744, 3.744, 3.744, 3.744, 3.744, 3.744, 3.763, 
3.783, 3.763, 3.744, 3.744, 3.744, 3.744, 3.763, 3.763, 3.763, 
3.763, 3.744, 3.744, 3.744, 3.744, 3.744, 3.744, 3.763, 3.783, 
3.831, 3.806, 3.783, 3.783), CritStatisticNeg = c(-3.763, -3.763, 
-3.763, -3.763, -3.763, -3.763, -3.763, -3.744, -3.744, -3.744, 
-3.744, -3.744, -3.744, -3.744, -3.744, -3.744, -3.744, -3.744, 
-3.744, -3.744, -3.744, -3.763, -3.744, -3.744, -3.744, -3.763, 
-3.744, -3.744, -3.744, -3.744, -3.744, -3.744, -3.763, -3.783, 
-3.763, -3.744, -3.744, -3.744, -3.744, -3.763, -3.763, -3.763, 
-3.763, -3.744, -3.744, -3.744, -3.744, -3.744, -3.744, -3.763, 
-3.783, -3.831, -3.806, -3.783, -3.783), PositiveRuns = c(NA, 
NA, NA, NA, NA, NA, NA, NA, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, NA, NA, NA, NA, NA, 2, 2, 2, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA), NegativeRuns = c(NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_)), .Names = c("Estimate", "StdErr", "Statistic", 
"Prob", "DF", "Time", "CritStatisticPos", "CritStatisticNeg", 
"PositiveRuns", "NegativeRuns"), eyetrackingR = structure(list(
    data_options = structure(list(participant_column = "ParticipantName", 
        trackloss_column = "TrackLoss", time_column = "TimeFromTrialOnset", 
        trial_column = "Trial", item_columns = NULL, aoi_columns = c("Animate", 
        "Inanimate"), treat_non_aoi_looks_as_missing = TRUE), .Names = c("participant_column", 
    "trackloss_column", "time_column", "trial_column", "item_columns", 
    "aoi_columns", "treat_non_aoi_looks_as_missing")), summarized_by = "ParticipantName", 
    time_bin_size = 100, formula = Prop ~ Target, p_adjust_method = "none", 
    alpha = 0.000909090909090909, threshold = NULL, test = "t.test", 
    predictor = "Target", positive_runs = list(structure(list(
        start_time = 16300, stop_time = 17700), .Names = c("start_time", 
    "stop_time")), structure(list(start_time = 18200, stop_time = 18500), .Names = c("start_time", 
    "stop_time"))), negative_runs = list()), .Names = c("data_options", 
"summarized_by", "time_bin_size", "formula", "p_adjust_method", 
"alpha", "threshold", "test", "predictor", "positive_runs", "negative_runs"
)), row.names = c(NA, 55L), class = c("bin_analysis", "data.frame"
))
